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  • 1
    Publication Date: 2024-02-29
    Description: In dieser Abschrift der Bergordnung wurden zur besseren Übersicht noch einmal die 23 Paragrafen der Kremnitzer Bergordnung von 1492 aufgeführt. Im Jahr 1504 wurden drei Paragrafen hinzugefügt. Im Jahr 1537 erließ Oberkammergrafen Bernhard Behem weitere 21 Paragrafen. Der Bergmeister wurde hier zur obersten Amtsperson im Revier erklärt und entsprechend vereidigt. Beschrieben wurden ausführlich seine Rechte und Pflichten.
    Description: source
    Keywords: Slowakei ; Ungarn ; Kremnitz/Kremnica ; Silberbergbau ; Bergordnung
    Language: German
    Type: doc-type:book , updatedVersion
    Format: 20
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  • 2
    Publication Date: 2024-02-21
    Description: Diese Bergordnung, erlassen im Jahr 1520, wiederholt die 103 Paragrafen der Annaberger Bergordnung aus dem Jahr 1509 sowie die dort aufgeführten Eide. Zusätzlich wurden ihr weitere 32 Paragrafen hinzugefügt, die in der Zeit zwischen 1510 und 1519 erlassen wurden. Mit dem Druck der neuen Bergordnung wollte man den Text der alten Bergordnung und die inzwischen erlassenen Paragrafen in einem Buch zusammenfassen. Obwohl auch in den neuen Paragrafen immer wieder Bezug auf Annaberg genommen wurde, war es aber schon in der Einleitung deutlich, dass diese Bergordnung für die gesamte Grafschaft Sachsen Gültigkeit hatte. Ausgenommen, waren auch hier die Bergwerke in Freiberg.
    Description: source
    Keywords: Herzog Georg von Sachsen ; Annaberg ; Freiberg ; Dresden ; Sachsen ; Silberbergbau ; Bergordnung
    Language: German
    Type: doc-type:book , updatedVersion
    Format: 47
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  • 3
    Publication Date: 2024-02-07
    Description: Diese Bergordnung für Schemnitz/Banská Štiavnica wurde im Jahr 1513 veröffentlicht. Sie wiederholt die Bergordnung von Schemnitz aus dem Jahr 1466. Danach werden neun weitere Artikel hinzugefügt. Sie präzisieren die Rechte der einzelnen Gruben beim Anschaaren von zwei Gängen und das Prozedere der Vermessung dieser Gänge.
    Description: source
    Keywords: König Bela IV. von Ungarn ; König Vladislav II. von Böhmen und Ungarn ; Slowakei ; Ungarn ; Schemnitz/Banská Štiavnica ; Silberbergbau ; Bergordnung
    Language: German
    Type: doc-type:book , updatedVersion
    Format: 11
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  • 4
    Publication Date: 2024-01-04
    Description: Um das Jahr 1540 erließen die Herren zu Franckenstein und die Herren von Heusenstamm eine Bergordnung für die Bergwerke in Espa im Taunus. Als Vorlage für diese Bergordnung diente eine Abschrift der Bergordnung der Grafen von Hohnstein vom 3. Februar 1528 für die Bergwerke in der Grafschaft Lauterberg. Es wurden aber nicht alle Paragrafen übernommen. Es fehlen eine Abschlusserklärung mit den Anwendungsbestimmungen sowie ein Datum zum Erlass dieser Bergordnung. Wahrscheinlich handelt es sich bei dieser Bergordnung um einen unveröffentlichten Entwurf. Eine weitere Bergordnung für dieses Gebiet ist aber nicht bekannt.
    Description: source
    Keywords: Herren zu Frankenstein ; Herren zu Heusenstamm ; Espa (Langgöns) ; Silberbergbau ; Bergordnung
    Language: German
    Type: doc-type:book , updatedVersion
    Format: 21
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  • 5
    Publication Date: 2024-01-11
    Description: Im Jahr 1529 erließ Herzog Georg von Sachsen eine neue Bergordnung für die Bergwerke in Freiberg. Im Gegensatz zum Erzgebirge, wo die 1509 erlassene Annaberger Bergordnung allgemeine Gültigkeit erlangt hatte, beharrte der Rat zu Freiberg auf ein in Teilen eigenständiges Bergrecht für die Stadt. Die Freiberger Bergordnung wurde vom Rat zu Freiberg gemeinsam mit den Gewerken im Beisein von Herzog Georg erstellt. In den 38 Artikeln wurde im Wesentlichen der Inhalt der Annaberger Bergordnung wiederholt. Neu für Freiberg war die Abrechnung und Austeilung sowie Veranschlagung der Zubuße in einem festgesetzten Zeitraum. Im Gegensatz zur Abrechnung in vier Quartalen, wie es im Erzgebirge seit 1476 Vorschrift war, erfolgte diese in Freiberg zu drei Terminen im Jahr. Weiterhin wurde darauf verwiesen, dass die Freiberger Bergbeamten die Eide analog der Annaberger Bergordnung leisten sollten.
    Description: source
    Keywords: Herzog Georg von Sachsen ; Freiberg ; Annaberg ; Silberbergbau ; Sachsen ; Bergordnung
    Language: German
    Type: doc-type:book , updatedVersion
    Format: 11
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  • 6
    Publication Date: 2024-04-25
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Mercury is the smallest and innermost planet of our solar system and has a dipole‐dominated internal magnetic field that is relatively weak, very axisymmetric and significantly offset toward north. Through the interaction with the solar wind, a magnetosphere is created. Compared to the magnetosphere of Earth, Mercury's magnetosphere is smaller and more dynamic. To understand the magnetospheric structures and processes we use in situ MESSENGER data to develop further a semi‐empiric model of the magnetospheric magnetic field, which can explain the observations and help to improve the mission planning for the BepiColombo mission en‐route to Mercury. We present this semi‐empiric KTH22‐model, a modular model to calculate the magnetic field inside the Hermean magnetosphere. Korth et al. (2015, 〈ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1002/2015JA021022"〉https://doi.org/10.1002/2015JA021022〈/ext-link〉, 2017, 〈ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1002/2017gl074699"〉https://doi.org/10.1002/2017gl074699〈/ext-link〉) published a model, which is the basis for the KTH22‐model. In this new version, the representation of the neutral sheet current magnetic field is more realistic, because it is now based on observations rather than ad‐hoc assumptions. Furthermore, a new module is added to depict the eastward ring shaped current magnetic field. These enhancements offer the possibility to improve the main field determination. In addition, analyzing the magnetic field residuals allows us to investigate the field‐aligned currents and their possible dependencies on external drivers. We see increasing currents under more disturbed conditions inside the magnetosphere, but no clear dependence on the z‐component of the interplanetary magnetic field nor on the magnetosheath plasma 〈italic〉β〈/italic〉.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉We present a revised model of Mercury's magnetospheric magnetic field〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉The model now includes an eastward ring shaped current and the neutral sheet current is calculated more precisely with Biot Savart's law〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉The strength of the field‐aligned currents increases with higher magnetic activity〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: German Ministerium für Wirtschaft und Klimaschutz and the German Zentrum für Luft‐ und Raumfahrt
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: ESA Research Fellowship
    Keywords: ddc:523 ; Mercury ; magnetosphere ; field‐aligned currents ; modeling ; neutral sheet current ; planetary dipole moment
    Language: English
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  • 7
    Publication Date: 2024-04-25
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Recent observations and modeling increasingly reveal the key role of cold pools in organizing the convective cloud field. Several methods for detecting cold pools in simulations exist, but are usually based on buoyancy fields and fall short of reliably identifying the active gust front. The current cold pool (CP) detection and tracking algorithm (CoolDeTA), aims to identify cold pools and follow them in time, thereby distinguishing their active gust fronts and the “offspring” rain cells generated nearby. To accomplish these tasks, CoolDeTA utilizes a combination of thermodynamic and dynamical variables and examines the spatial and temporal relationships between cold pools and rain events. We demonstrate that CoolDeTA can reconstruct CP family trees. Using CoolDeTA we can contrast radiative convective equilibrium (RCE) and diurnal cycle CP dynamics, as well as cases with vertical wind shear and without. We show that the results obtained are consistent with a conceptual model where CP triggering of children rain cells follows a simple birth rate, proportional to a CP's gust front length. The proportionality factor depends on the ambient atmospheric stability and is lower for RCE, in line with marginal stability as traditionally ascribed to the moist adiabat. In the diurnal case, where ambient stability is lower, the birth rate thus becomes substantially higher, in line with periodic insolation forcing—resulting in essentially run‐away mesoscale excitations generated by a single parent rain cell and its CP.〈/p〉
    Description: Plain Language Summary: Cold pools are cooled air masses below thunderstorm clouds, produced when rain evaporates underneath such clouds. Cold pools are important, as they produce strong gusts and have been associated with clumping of rain cells, whereby heavy rainfall over relatively small areas could be generated—with implications for flooding. The current work describes a method that helps identify such cold pools in computer simulation data. In contrast to earlier methods, we here show that the interaction between a CP and its surroundings can be reconstructed by the method. We show that this identification works under a range of contexts, such as when horizontal wind is applied in the simulations or when the surface temperature is not constant—as might often be the case over a land surface. The identification reveals interesting dynamical effects, such as that in some cases, cold pools can kick‐start a form of chain reaction, by which “rain cell children” of it give rise to additional cold pools that again produce children, and so forth. The dynamics revealed is in line with expectations of widespread, so‐called mesoscale convective systems over land, whereas over an ocean surface the dynamics is much less explosive.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉Our CoolDeTA algorithm reliably detects and tracks cold pools and their causal chains〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉We propose a simple conceptual model which reproduces the cascade‐like mesoscale cold pool dynamics identified by CoolDeTA〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉CoolDeTA opens for new studies into the dynamics of convective self‐organization through cold pools〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: Villum Fonden http://dx.doi.org/10.13039/100008398
    Description: European Research Council http://dx.doi.org/10.13039/501100000781
    Description: Novo Nordisk Foundation Interdisciplinary Synergy Program
    Description: Scientific Steering Committee
    Description: https://doi.org/10.5281/zenodo.6513224
    Description: https://github.com/Shakiro7/coldPool-detection-and-tracking
    Description: https://doi.org/10.5281/zenodo.10115957
    Description: https://doi.org/10.7717/peerj.453
    Keywords: ddc:551.6 ; cold pools ; detection ; tracking ; cloud resolving simulation ; convective organization
    Language: English
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  • 8
    Publication Date: 2024-04-25
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉The seasonal deposition and sublimation of CO〈sub〉2〈/sub〉 constitute a major element in the Martian volatile cycle. Here, we propose to use the shadow variations of the ice blocks at the foot of the steep scarps of the North Polar Layered Deposits (NPLD) to infer the vertical evolution of the seasonal deposits. We conduct an experiment at a steep scarp centered at (85.0°N, 151.5°E). We assume that no snowfall remains on top of the selected ice blocks, the frost ice layer is homogeneous around the ice blocks and their surroundings, and no significant moating is present. We show that the average thickness of the seasonal deposits due to snowfalls in Mars Year 31 is 0.97 ± 0.13 m at Ls = 350.7° in late winter. The large depth measured makes us wonder if snowfalls are more frequent and violent than previously thought. Meanwhile, we show that the average frost thickness in Mars Year 31 reaches 0.64 ± 0.18 m at Ls = 350.7° in late winter. Combined, the total thickness of the seasonal cover in Mars Year 31 reaches 1.63 ± 0.22 m at Ls = 350.7° in late winter, continuously decreases to 0.45 ± 0.06 m at Ls = 42.8° in middle spring and 0.06 ± 0.05 m at Ls = 69.6° in late spring. These estimates are up to 0.8 m lower than the existing Mars Orbiter Laser Altimeter results during the spring. Meanwhile, we observe that snow in the very early spring of Mars Year 36 can be 0.36 ± 0.13 m thicker than that in Mars Year 31. This study demonstrates the dynamics of the Martian climate and emphasizes the importance of its long‐term monitoring.〈/p〉
    Description: Plain Language Summary: Like Earth, Mars also has seasons. Up to one third of the atmospheric CO〈sub〉2〈/sub〉 annually exchanges with the polar surface through seasonal deposition/sublimation processes. Deposition can be either atmospheric precipitation as snowfall or direct surface condensation as frost. At the steep scarps of the North Polar Layered Deposits (NPLD), fractured ice fragments can detach and fall to form ice blocks. We propose to use variations in the shadows of these ice blocks, observed in the High Resolution Imaging Science Experiment images, to infer the thickness evolution of the seasonal deposits. We make reasonable assumptions about the distribution of snowfall and frost around the ice blocks and their surroundings, which allow us to separately measure the thickness of snowfall and frost. Meanwhile, we introduce a novel approach that allows us to estimate the thickness of the seasonal deposits during late winter and early spring when image quality is insufficient. This approach also enables us to peer into the interannual thickness variations of snowfall. We carry out a successful experiment at a scarp centered at (85.0°N, 151.5°E). The obtained thickness measurements demonstrate the dynamics of the Martian volatile cycling and can be used to constrain the Martian climate models.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉We propose to examine the shadow variations of the ice blocks at the Martian polar region to infer the thickness of the seasonal deposits〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉Maximum thickness of the seasonal deposits at the study scarp in MY31 is 1.63 ± 0.22 m to which snowfalls contribute 0.97 ± 0.13 m〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉Seasonal deposits at the study scarp are up to 0.8 m shallower than previous measurements during spring〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: HX, LML, and PJG
    Description: https://doi.org/10.17189/1520303
    Description: https://doi.org/10.17632/5yy475dbry.1
    Description: https://doi.org/10.17632/x953mzxxvv.1
    Description: https://doi.org/10.17189/1520101
    Description: http://www.msss.com/moc_gallery/2001
    Keywords: ddc:523 ; Mars ; seasonal polar caps ; thickness ; ice blocks ; HiRISE ; CO2
    Language: English
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  • 9
    Publication Date: 2024-04-25
    Description: 〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉〈italic〉INSIGHT〈/italic〉 is a Python‐based software tool for processing and reducing 2D grazing‐incidence wide‐ and small‐angle X‐ray scattering (GIWAXS/GISAXS) data. It offers the geometric transformation of the 2D GIWAXS/GISAXS detector image to reciprocal space, including vectorized and parallelized pixel‐wise intensity correction calculations. An explicit focus on efficient data management and batch processing enables full control of large time‐resolved synchrotron and laboratory data sets for a detailed analysis of kinetic GIWAXS/GISAXS studies of thin films. It processes data acquired with arbitrarily rotated detectors and performs vertical, horizontal, azimuthal and radial cuts in reciprocal space. It further allows crystallographic indexing and GIWAXS pattern simulation, and provides various plotting and export functionalities. Customized scripting offers a one‐step solution to reduce, process, analyze and export findings of large 〈italic〉in situ〈/italic〉 and 〈italic〉operando〈/italic〉 data sets.〈/p〉
    Keywords: ddc:548 ; grazing‐incidence X‐ray scattering ; time‐resolved studies ; in situ studies ; operando studies ; computer programs
    Language: English
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  • 10
    Publication Date: 2024-04-25
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Dansgaard‐Oeschger (D‐O) climate variability during the last glaciation was first evidenced in ice cores and marine sediments, and is also recorded in various terrestrial paleoclimate archives in Europe. The relative synchronicity across Greenland, the North Atlantic and Europe implies a tight and fast coupling between those regions, most probably effectuated by an atmospheric transmission mechanism. In this study, we investigated the atmospheric changes during Greenland interstadial (GI) and stadial (GS) phases based on regional climate model simulations using two specific periods, GI‐10 and GS‐9 both around 40 ka, as boundary conditions. Our simulations accurately capture the changes in temperature and precipitation as reconstructed by the available proxy data. Moreover, the simulations depict an intensified and southward shifted eddy‐driven jet during the stadial period. Ultimately, this affects the near‐surface circulation toward more southwesterly and cyclonic flow in western Europe during the stadial period, explaining much of the seasonal climate variability recorded by the proxy data, including oxygen isotopes, at the considered proxy sites.〈/p〉
    Description: Plain Language Summary: The climate during the last ice age varied between colder and warmer periods on timescales ranging from hundreds to thousands of years. This variability was first detected in Greenland ice cores and marine sediment cores of the North Atlantic, as well as in continental geological records in Europe. The variation between the colder and warmer periods occur mostly simultaneously in Greenland and in Europe, which is why the atmosphere is assumed to have an important role in transferring the climate signals. We simulated two different periods of the last ice age, one colder and one warmer around 40,000 years ago, using a regional climate model. The aim was to study how the climate and atmospheric circulation changed during these two periods. We find the eddy‐driven jet over the North Atlantic intensified and shifted southward during the colder period. The jet influences the near‐surface atmospheric circulation and leads to more southwesterly and cyclonic flow in western Europe. Oxygen isotope variations observed in western European paleoclimate records may be partly explained by different, more southern moisture sources on top of changes in seasonal temperatures.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉Simulated temperatures agree with proxy data; precipitation is biased but GI‐10 versus GS‐9 differences are well captured〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉The stadial winter jet stream is intensified and shifted southward, consistent with dominant southwesterly/cyclonic flow in western Europe〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉Oxygen isotope signal changes at western European proxy sites may be explained not only by temperature but also by varying moisture sources〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: NRDIO
    Description: AXA Research Fund http://dx.doi.org/10.13039/501100001961
    Description: https://doi.org/10.5065/1dfh-6p97
    Keywords: ddc:551.6 ; Dansgaard‐Oeschger cycle ; regional atmospheric dynamics ; regional climate modeling ; continental paleoclimate proxy ; Europe
    Language: English
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  • 11
    Publication Date: 2024-01-18
    Description: Die Bergordnung für Schemnitz/Banská Štiavnica wurde im Jahr 1466 als Anhang zum Stadtrecht im Stadtbuch (1432 begonnen) niedergeschrieben. Von den 59 Paragrafen waren nur die Paragrafen 42 bis 59 für das das Bergrecht relevant. Die Entstehungszeit der Bergordnung geht auf die Regierungszeit König Béla IV. (1235-1270) zurück. Nach der Einleitung durch König Béla IV. beschreiben die Geschworenen der Stadt die Verleihung von Gruben, die Rechte und Pflichten beim Betrieb der Bergwerke, das Stollenrecht und die Vermessung der Gruben. Im Gegensatz zu späteren Bergordnungen wurden hier nicht aufgetretene Fehlentwicklungen geregelt, sondern bereits klare gesetzliche Regelungen für den Bergbau vorgegeben.
    Description: source
    Keywords: König Béla IV. von Ungarn ; Slowakei ; Ungarn ; Schemnitz/Banská Štiavnica ; Iglau/Jihlava ; Silberbergbau ; Bergordnung
    Language: German
    Type: doc-type:book , updatedVersion
    Format: 9
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  • 12
    Publication Date: 2024-01-28
    Description: Diese im Jahr 1536 neu verfasste Bergordnung für Freiberg, erlassen von Herzog Georg von Sachsen wiederholt die 38 Artikel der Bergordnung von 1529. Zwischen 1530 und 1536 wird sie um vier weitere Artikel, unterteilt in 24 Absätze und einen Nachsatz, erweitert. Aus den angefügten Artikeln geht hervor, das die Bergordnung von 1529 nur widerwillig umgesetzt wurde. Die alte Bergordnung wird präzisiert, ein Hüttenraiter eingeführt und der Freiberger Rat mit Nachdruck aufgefordert die Durchsetzung der Bergordnung streng zu befolgen.
    Description: source
    Keywords: Herzog Georg von Sachsen ; Freiberg ; Annaberg ; Silberbergbau ; Sachsen ; Bergordnung
    Language: German
    Type: doc-type:book , updatedVersion
    Format: 16
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  • 13
    Publication Date: 2024-03-22
    Description: Obwohl die Wettiner das Gebiet um Berggießhübel und Gottleuba schon 1405 übernommen haben, wurde erst 1516 eine Bergordnung für den dortigen Eisenerzbergbau erlassen. In den vier Paragrafen geht es um Zustand der Bergwerke, das ordentliche Vermessen der Gruben und die Zahlung des Zehnten. Weiterhin soll der offensichtlich dauerhafte Streit zwischen den Gewerken und den Hammermeistern um Menge und Qualität des Eisensteins beendet werden.
    Description: source
    Keywords: Herzog Georg von Sachsen ; Freiberg ; Pirna ; Berggießhübel ; Bad Gottleuba ; Eger/Cheb ; Sachsen ; Eisenerzbergbau ; Bergordnung
    Language: German
    Type: doc-type:book , updatedVersion
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  • 14
    Publication Date: 2024-04-03
    Description: In der Bohrung Moosburg 4 wurden die Nichtkarbonate (HCl-Unlösliches; 45 Proben) der Karbonatgesteine vom Malm Alpha (Unteres Oxfordium) bis zum Malm Zeta (Oberes Tithonium) röntgendiffraktometrisch untersucht. Ziel war es, die bestehende lithostratigraphische Untergliederung genauer mineralogisch und tonmineralogisch zu untermauern, um diese in Malm-Bohrungen des Molasse-Untergrundes besser belegen zu können. Die Kombination von mineralogischen und tonmineralogischen röntgenographischen Untersuchungen der Nichtkarbonate ermöglichen es, unter Bezug zum Gamma-Log der Bohrung Moosburg SC4 eine Untergliederung in neun Einheiten (I – IX) zu definieren. Diese entspricht vom Malm Alpha bis Malm Zeta 3 weitgehend der lithostratigraphischen Unterteilung, wie sie von Meyer (1994) dokumentiert wird. Die von Meyer (1994) vorgenommene Positionierung des Malm Zeta 4-5 und die der als Purbeck definierten Schichtfolge müssen dagegen revidiert werden. Die Malm/ Purbeck-Grenze ist um 99 m ins Hangende zu legen. Damit entspricht der dort im Malm analysierte Bereich dem Untertithon und dem Obertithon. Karbonatgesteine des Purbeck wurden in der vorliegenden Studie nicht untersucht. Die Zuordnung der Einheiten I-VI zu den lithostratigraphischen Einheiten von Meyer (1994) ist gut. Es ist nur der obere Teil der Bohrung Moosburg 4 als Unteres und als Oberes Tithon neu zu definieren. Allgemein kann festgestellt werden, dass eine lithostratigraphische Untergliederung des Malm auf der Basis mineralogisch/tonmineralogischer Analysen der Nichtkarbonate erstellt werden kann. Diese Methode kann daher auch in neuen Bohrungen im Molassebecken zur Untergliederung der oberjurassischen Schichtfolge erfolgreich angewendet werden.
    Description: research
    Keywords: Ober-Jura ; Tonmineral-Stratigraphie ; Mineralostratigraphie
    Language: German
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  • 15
    Publication Date: 2024-04-03
    Description: Bergordnung für St. Joachimsthal, vom 2. August 1518. Basis dieser Bergordnung bildet die Bergordnungen für St. Annaberg vom 5. Februar 1509. Die 103 Paragraphen der Annaberger Bergordnung wurden fast wortwörtlich übernommen. Es wurde der gesamte Bergwerksbetrieb, die Arbeit der Schmelzhütten und das Gericht in St. Joachimsthal geregelt. Auch die Eide der Bergbeamten wurden übernommen. In weiteren drei Paragraphen wurden die Entlohnung der Bergleute sowie die Lohnfortzahlung und das Arztgeld nach Arbeitsunfällen aufgeführt.
    Description: source
    Keywords: Graf Stefan Schlick zu Passaun ; Konradsgrün ; Joachimsthal/Jáchymov ; Annaberg ; Marienberg ; Schneeberg ; Silberbergbau ; Böhmen ; Bergordnung
    Language: German
    Type: doc-type:book , updatedVersion
    Format: 39
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  • 16
    Publication Date: 2024-04-03
    Description: Tiefgreifende Hangbewegungen stellen neben Muren und Lawinen, welche durch Faktoren wie Extremniederschlagsereignisse und Unterschneidungsvorgänge entstehen, eine akute Gefahr für die Bevölkerung und die Infrastruktur im alpinen Raum dar (Moser 2013). Talzuschübe, oder auch DSGSD für Deep-seated Gravitational Slope Deformation (Crosta et al. 2013), sind großflächige und tiefgreifende Hangbewegungen im alpinen Raum. Im Rahmen dieser Untersuchungen erfolgte eine ingenieurgeologische Aufnahme des Dürnbachtals bei Neukirchen am Großvenediger mit der Erstellung von Hangprofilen und der Aufnahme des Trennflächengefüges. Weiter wurde der Einfluss der beidseitigen Talzuschübe auf den Wildbach und das Murereignis nach einem Starkniederschlagsereignis am 28.07.2022 analysiert. Zuletzt wurde eine Abschätzung des Gefahrenpotentials des Dürnbachs für den Ort Neukirchen am Großvenediger erstellt.
    Description: research
    Keywords: Talzuschub ; counterscarps ; Massenbewegung ; Murgang ; Starkniederschlag ; Salzburger Land ; Österreich
    Language: German
    Type: doc-type:article
    Format: 41
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  • 17
    Publication Date: 2024-04-19
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Heavy‐mineral suites are used widely in sandstone provenance and are key when connecting source and sink. When characterizing provenance related signatures, it is essential to understand the different factors that may influence a particular heavy‐mineral assemblage for example, chemical weathering or diagenetic processes. Hydrodynamics, causing size‐density sorting, exert major control on the distribution of heavy minerals. Here, we highlight the effect of grain‐size inheritance, essentially the absence of certain grain sizes within a specific heavy‐mineral species, on two distinct types of sediments. Modern deposits from a high‐energy beach in NW Denmark give an analog for heavily reworked sediment, primarily controlled by hydrodynamic processes. In contrast, three Palaeogene turbidite successions in the Eastern Alps were sampled, presenting a more complex history that includes diagenesis. All samples were processed for their heavy‐mineral compositions using Raman spectroscopy, and several techniques applied to determine the effect of grain‐size inheritance. Results show that (a) even within the hydrodynamically well‐sorted beach and placer deposits, evidence of grain‐size inheritance is apparent, and (b) turbidites of variable heavy‐mineral composition show strong effects of grain‐size inheritance for several mineral species. Moreover, considerable intersample contrasts within single turbidite beds are observed. We enforce the importance of understanding grain‐size inheritance, as well as other processes effecting size‐density relations in clastic sediment that go well beyond purely hydrodynamic control of intrasample heavy‐mineral variability.〈/p〉
    Description: Plain Language Summary: Heavy minerals are commonly found within sediments and sedimentary rocks and can tell us from which source regions the sediment may have originated. However, it is important to understand that the type, size, and abundance of particular heavy minerals can change depending on factors such as environmental conditions. The size, shape, and density of the heavy minerals also limits when and where they will settle and/or stay. A lack of big or small grains of a particular heavy mineral in the source rocks dictates the size of the minerals deposited; this is known as grain‐size inheritance. Using both ancient and modern sediment, we are looking for traces of grain‐size inheritance. Surprisingly, in all samples investigated we noted effects of grain‐size inheritance, for different heavy‐mineral types. The modern beach sediments, as expected, show more impact of hydraulic processes, but inherited grain sizes are still apparent. Within the ancient examples, grain‐size inheritance is more obvious, with further variations even observed between samples collected from the same area. Having identified this control on grain size, we can highlight the importance of understanding this effect when analyzing clastic sediments.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉Understanding factors that can modify a heavy‐mineral assemblage is fundamental in provenance analysis〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉Heavy minerals of two distinct sedimentary environments were analyzed and compared to their “ideal” hydrodynamically sorted compositions〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉Several heavy‐mineral species of modern and ancient settings were identified to be influenced by grain‐size inheritance from the source〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: https://doi.org/10.25625/MVUIJQ
    Keywords: ddc:552.5 ; heavy minerals ; provenance ; grain‐size inheritance ; hydrodynamics ; diagenesis
    Language: English
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  • 18
    Publication Date: 2024-04-19
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉The Ismenius Lacus region of Mars has a diverse geological history, and we present the first high‐resolution map of Deuteronilus Cavus (36.2°N; 14.0°E, ∼120 km diameter) in the fretted terrain south of the dichotomy boundary. Strong evidence suggests a volcanic origin of the regional plains, based on the ∼50 m thick volcanic bed underlying 180–300 m of sublimation residue associated with Amazonian plateau glaciation. Pervasive external volcanic flooding, internal erosional modification, and enlargement of a pre‐existing crater by up to 175%–200% resulted in the cavus' present shape. The phyllosilicates detected within Deuteronilus Cavus could be primary materials associated with the surficial aqueous activity, subsurface alteration products excavated by impacts, or a combination of both. We observe branching fluvial channels that are more recent than the traditional valley networks and may be related to fretted terrain resurfacing during the waning period of a high‐obliquity glaciation phase. This is consistent with our interpretation of the ∼600 m thick lobate and lineated deposits, which are remnants of receding glaciers. The glacial ice, protected by a 15–20 m insulating layer of debris cover, is of significant interest for future landing missions because of its potential to preserve biological and climatological signatures, to provide a critical test of Amazonian plateau glaciation, and to be used for in situ resource utilization. With our detailed geological mapping, we improved our understanding of the geological evolution and climatic conditions in the enigmatic fretted terrain near the dichotomy boundary.〈/p〉
    Description: Plain Language Summary: The ∼120 km long Deuteronilus Cavus was initiated by an impact event. The resulting impact crater was modified by glacial erosional and fluvial processes, leading to the enlargement of 175%–200% of the pre‐existing crater. In addition, we find strong evidence for recent glaciation (〈1 Ga) that left 180–300 m of sublimation residue on the plateau superimposed on a ∼50 m thick volcanic bed, suggesting a volcanic origin of the regional plains. During the waning period of a high‐glacial phase, the meltwater ponded on the surface of the cavus, altered surface rocks to produce phyllosilicates, formed channels (now observed as inverted sinuous ridges), and locally distributed branched fluvial channels that are more recent than the traditional valley networks. Glacial landforms still contain up to 600 m of remnant ice from the retreating glaciers at the end of the last glacial period. The relatively pure ice, protected by a 15–20 m insulating layer of debris cover, is critical for future landing missions because of its potential to preserve biological and climatological signatures and to be used for in situ resource utilization. Overall, this research enhances our understanding of the geological evolution and climatic history of Mars.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉We have produced the first high‐resolution map of Deuteronilus Cavus in the fretted terrain south of the Martian dichotomy boundary〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉The region records a complex erosional and depositional history, including fluvial and glacial processes in the Amazonian period〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉This study provides a framework for exploration of high‐obliquity mid‐latitude plateau glaciation〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: Deutsches Zentrum für Luft‐ und Raumfahrt http://dx.doi.org/10.13039/501100002946
    Description: https://doi.org/10.5281/zenodo.8205276
    Description: https://doi.org/10.17189/1520332
    Description: https://doi.org/10.17189/1520266
    Description: https://doi.org/10.17189/1520303
    Description: https://doi.org/10.5270/esa-pm8ptbq
    Keywords: ddc:523 ; Mars ; Deuteronilus Cavus ; geological mapping ; glaciation
    Language: English
    Type: doc-type:article
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  • 19
    Publication Date: 2024-04-20
    Description: Im Zusammenhang mit der Neuordnung der Bergverwaltung fand auch in Berggießhübel eine Besichtigung der Bergwerke statt. Aufgrund der festgestellten Unregelmäßigkeiten wurde eine neue Bergordnung erlassen. In 11 Paragrafen wurde eine ordentliche Rechnungslegung festgelegt, die Hammerherren zur pünktlichen Bezahlung des Eisensteins aufgefordert und eine strenge Kontrolle der Arbeitszeit angeordnet. Weiterhin erhielten Gewerken eine Steuererleichterung beim Stollnvortrieb.
    Description: source
    Keywords: Herzog Moritz von Sachsen ; Dresden ; Pirna ; Berggießhübel ; Gottleuba ; Sachsen ; Eisenerzbergbau ; Bergordnung
    Language: German
    Type: doc-type:book , updatedVersion
    Format: 7
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  • 20
    Publication Date: 2024-05-11
    Description: Diese Bergordnung wurde am 5. Januar 1517 von Maximilian I., Römisch deutscher Kaiser und König sowie Erzherzog von Österreich, für die Bergwerke in Österreich, der Steiermark, Kärnten und Krain erlassen. Die mit 271 Paragrafen sehr umfangreiche Bergordnung basiert auf dem Bergrecht von Iglau und der Bergordnung für Schwaz von 1490. Sie ist in acht Abschnitte gegliedert. Geregelt werden alle den Bergbau betreffende Maßnahmen. Angefangen über die Festlegung der Grubenmaße, die Rechte und Pflichten der Bergbeamten, Bergleute, Schmiede und Schmelzer, die Arbeitszeiten und Bezahlung, die Holzrechte bis hin zur Führung von Gerichtsprozessen über Streitigkeiten und deren Kosten.
    Description: source
    Keywords: Maximilian I. ; Österreich ; Steiermark ; Kärnten ; Krain ; Friesach ; Frohnleiten ; Glödnitz ; Meislding ; Obervellach ; Rottenmann ; Schladming ; Schrems ; Seckau ; St. Paul bei Hornburg ; St. Veit an der Glan ; Villach ; Waitschach ; Windisch Bleiberg ; Zeiring ; Zeltschach ; Schwaz ; Iglau/Jihlava ; Silberbergbau ; Bergordnung
    Language: German
    Type: doc-type:book , updatedVersion
    Format: 49
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  • 21
    Publication Date: 2024-05-22
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Mineral dust is one of the most abundant atmospheric aerosol species and has various far‐reaching effects on the climate system and adverse impacts on air quality. Satellite observations can provide spatio‐temporal information on dust emission and transport pathways. However, satellite observations of dust plumes are frequently obscured by clouds. We use a method based on established, machine‐learning‐based image in‐painting techniques to restore the spatial extent of dust plumes for the first time. We train an artificial neural net (ANN) on modern reanalysis data paired with satellite‐derived cloud masks. The trained ANN is applied to cloud‐masked, gray‐scaled images, which were derived from false color images indicating elevated dust plumes in bright magenta. The images were obtained from the Spinning Enhanced Visible and Infrared Imager instrument onboard the Meteosat Second Generation satellite. We find up to 15% of summertime observations in West Africa and 10% of summertime observations in Nubia by satellite images miss dust plumes due to cloud cover. We use the new dust‐plume data to demonstrate a novel approach for validating spatial patterns of the operational forecasts provided by the World Meteorological Organization Dust Regional Center in Barcelona. The comparison elucidates often similar dust plume patterns in the forecasts and the satellite‐based reconstruction, but once trained, the reconstruction is computationally inexpensive. Our proposed reconstruction provides a new opportunity for validating dust aerosol transport in numerical weather models and Earth system models. It can be adapted to other aerosol species and trace gases.〈/p〉
    Description: Plain Language Summary: Most dust and sand particles in the atmosphere originate from North Africa. Since ground‐based observations of dust plumes in North Africa are sparse, investigations often rely on satellite observations. Dust plumes are frequently obscured by clouds, making it difficult to study the full extent. We use machine‐learning methods to restore information about the extent of dust plumes beneath clouds in 2021 and 2022 at 9, 12, and 15 UTC. We use the reconstructed dust patterns to demonstrate a new way to validate the dust forecast ensemble provided by the World Meteorological Organization Dust Regional Center in Barcelona, Spain. Our proposed method is computationally inexpensive and provides new opportunities for assessing the quality of dust transport simulations. The method can be transferred to reconstruct other aerosol and trace gas plumes.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉We present the first fast reconstruction of cloud‐obscured Saharan dust plumes through novel machine learning applied to satellite images〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉The reconstruction algorithm utilizes partial convolutions to restore cloud‐induced gaps in gray‐scaled Meteosat Second Generation‐Spinning Enhanced Visible and Infrared Imager Dust RGB images〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉World Meteorological Organization dust forecasts for North Africa mostly agree with the satellite‐based reconstruction of the dust plume extent〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: GEOMAR Helmholtz Centre for Ocean Research Kiel
    Description: University of Cologne
    Description: https://doi.org/10.5281/zenodo.6475858
    Description: https://github.com/tobihose/Masterarbeit
    Description: https://dust.aemet.es/
    Description: https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-global-reanalysis-eac4?tab=overview
    Description: https://navigator.eumetsat.int/product/EO:EUM:DAT:MSG:DUST
    Description: https://navigator.eumetsat.int/product/EO:EUM:DAT:MSG:CLM
    Description: https://doi.org/10.5067/KLICLTZ8EM9D
    Description: https://disc.gsfc.nasa.gov/datasets?project=MERRA-2
    Description: https://doi.org/10.5067/MODIS/MOD08_D3.061
    Description: https://doi.org/10.5067/MODIS/MYD08_D3.061
    Description: https://doi.org/10.5281/ZENODO.8278518
    Keywords: ddc:551.5 ; mineral dust ; North Africa ; MSG SEVIRI ; machine learning ; cloud removal ; satellite remote sensing
    Language: English
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  • 22
    Publication Date: 2024-05-22
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Regardless of the steady increase of computing power during the last decades, numerical models in a 3D spherical shell are only used in specific setups to investigate the thermochemical convection in planetary interiors, while 2D geometries are typically favored in most exploratory studies involving a broad range of parameters. The 2D cylindrical and the more recent 2D spherical annulus geometries are predominantly used in this context, but the extent to how well they reproduce the 3D spherical shell results in comparison to each other and in which setup has not yet been extensively investigated. Here we performed a thorough and systematic study in order to assess which 2D geometry reproduces best the 3D spherical shell. In a first set of models, we investigated the effects of the geometry on thermal convection in steady‐state setups while varying a broad range of parameters. Additional thermal evolution models of three terrestrial bodies, namely Mercury, the Moon, and Mars, which have different interior structures, were used to compare the 2D and 3D geometries. Our investigations show that the 2D spherical annulus geometry provides results closer to models in a 3D spherical shell compared to the 2D cylindrical geometry. Our study indicates where acceptable differences can be expected when using a 2D instead of a 3D geometry and where to be cautious when interpreting the results.〈/p〉
    Description: Plain Language Summary: In geodynamic modeling, numerical models are used in order to investigate how the interior of a terrestrial planet evolves from the earliest stage, after the planetary formation, up to present day. Often, the mathematical equations that are used to model the physical processes in the interior of rocky planets are discretized and solved using geometric meshes. The most commonly applied geometries are the 3D spherical shell, the 2D cylinder, and the 2D spherical annulus. While being the most accurate and realistic, the 3D geometry is expensive in terms of computing power and time of execution. On the other hand, 2D geometries provide a reduced accuracy but are computationally faster. Here we perform an extensive comparison between 2D and 3D geometries in scenarios of increasing complexity. The 2D spherical annulus geometry shows much closer results to the 3D spherical shell when compared to the 2D cylinder and should be given preference in 2D modeling studies.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉Interior dynamics models using the 2D spherical annulus geometry match the results of a 3D spherical shell better than the 2D cylinder〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉The difference between 2D and 3D geometries decreases when models are heated from below by the core and from within by radioactive elements〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉The 2D spherical annulus shows negligible differences to 3D for the thermal evolution of Mercury and the Moon, and acceptable values for Mars〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: Ministry of Science, Research and the Arts Baden‐Württemberg
    Description: Federal Ministry of Education and Research
    Description: https://doi.org/10.5281/zenodo.8047757
    Keywords: ddc:523 ; mantle convection ; thermal evolution ; spherical annulus ; Mars ; Moon ; Mercury
    Language: English
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  • 23
    Publication Date: 2024-05-21
    Description: Das Deutsche Iglauer Bergrecht liegt in drei Varianten vor, die von Adolf Zycha entsprechend mit I, II und III bezeichnet wurden. Es entstand im 13. und 14. Jahrhundert. Die Abschriften Adolf Zychas beruhen auf Originalakten aus dem Ratsarchiv Freiberg und dem Stadtarchiv Iglau. In ihm wurden analog zu den Iglauer Bergrechten A und B die rechtlichen Regelungen für den Bergbau im Königreich Böhmen und der Markgrafschaft Mähren niedergeschriebenen. In der Variante II wurden zwei Paragrafen hinzugefügt und in der Variante III vierzehn Paragrafen. Elf Paragrafen der Variante III beinhalten Stadtrecht.
    Description: source
    Keywords: Böhmen ; Mähren ; Iglau/Jihlava ; Freiberg ; Silberbergbau ; Bergrecht
    Language: German
    Type: doc-type:book , updatedVersion
    Format: 24
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  • 24
    Publication Date: 2024-05-23
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉NASA's Juno mission delivered gravity data of exceptional quality. They indicate that the zonal winds, which rule the dynamics of Jupiter's cloud deck, must slow down significantly beyond a depth of about 3,000 km. Since the underlying inversion is highly non‐unique additional constraints on the flow properties at depth are required. These could potentially be provided by the magnetic field and its Secular Variation (SV) over time. However, the role of these zonal winds in Jupiter's magnetic field dynamics is little understood. Here we use numerical simulations to explore the impact of the zonal winds on the dynamo field produced at depth. We find that the main effect is an attenuation of the non‐axisymmetric field, which can be quantified by a modified magnetic Reynolds number Rm that combines flow amplitude and electrical conductivity profile. Values below Rm = 3 are required to retain a pronounced non‐axisymmetric feature like the Great Blue Spot (GBS), which seems characteristic for Jupiter's magnetic field. This allows for winds reaching as deep as 3,400 km. A SV pattern similar to the observation can only be found in some of our models. Its amplitude reflects the degree of cancellation between advection and diffusion rather than the zonal wind velocity at any depth. It is therefore not straightforward to make inferences on the deep structure of cloud‐level winds based on Jupiter's SV.〈/p〉
    Description: Plain Language Summary: The dynamics in Jupiter's cloud layer is dominated by eastward and westward directed wind jets that circumvent the planet and reach velocities of up to 150 m per second. For the first time, NASA's Juno mission could measure the tiny gravity changes caused by these winds. The data show that the winds reach down to a depth of about 3,000 km, roughly 4% of Jupiter's radius. However, the interpretation is difficult and several alternative wind profiles have been suggested. In this paper we use numerical simulations to explore how these winds would affect Jupiter's magnetic field, which has also been measured with high precision by Juno. The field shows a strong inward‐directed local patch just south of the equator, called the GBS. The impact of the winds on the magnetic field rapidly increases with depth because of the increase in the electrical conductivity. Our simulations show that winds reaching deeper than about 3,400 km would practically wipe out the GBS. This confirms that they have to remain shallower. Juno also observed an east‐ward drift of the GBS. While some of our simulations also show an east‐ward drift it is typically much too slow.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉We study the magnetic field variations caused by Jupiter's deep‐reaching surface winds for various flow and electrical conductivity models〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉Zonal winds reaching deeper than 3,400 km would yield a very axisymmetric surface field and are thus unrealistic〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉It seems questionable that Jupiter's secular variation carries any useful information on the zonal winds〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: Engineering and Physical Sciences Research Council http://dx.doi.org/10.13039/501100000266
    Description: https://doi.org/10.17617/3.CNVRWD
    Keywords: ddc:523 ; Jupiter ; magnetic field ; atmospheric dynamics ; zonal winds
    Language: English
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  • 25
    Publication Date: 2024-05-23
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉The microphysical structure of the lunar regolith provides information on the geologic history of the Moon. We used remote sensing measurements of thermal emission and a thermophysical model to determine the microphysical properties of the lunar regolith. We expand upon previous investigations by developing a microphysical thermal model, which more directly simulates regolith properties, such as grain size and volume filling factor. The modeled temperatures are matched with surface temperatures measured by the Diviner Lunar Radiometer Experiment on board the Lunar Reconnaissance Orbiter. The maria and highlands are investigated separately and characterized in the model by a difference in albedo and grain density. We find similar regolith temperatures for both terrains, which can be well described by similar volume filling factor profiles and mean grain sizes obtained from returned Apollo samples. We also investigate a significantly lower thermal conductivity for highlands, which formally also gives a very good solution, but in a parameter range that is well outside the Apollo data. We then study the latitudinal dependence of regolith properties up to ±80° latitude. When assuming constant regolith properties, we find that a variation of the solar incidence‐dependent albedo can reduce the initially observed latitudinal gradient between model and Diviner measurements significantly. A better match between measurements and model can be achieved by a variation in intrinsic regolith properties with a decrease in bulk density with increasing latitude. We find that a variation in grain size alone cannot explain the Diviner measurements at higher latitudes.〈/p〉
    Description: Plain Language Summary: The Moon is covered by a layer of fine grained material called regolith. To extract information about the regolith, such as grain size or stratification, we used data from the Diviner instrument on board the Lunar Reconnaissance Orbiter. Diviner measures the surface temperature of the regolith for each location on the Moon and all times during day and night. To derive regolith properties, we developed a model and varied its model parameters until the simulated surface temperatures matched the measured ones. We applied the model up to a latitude of 80° and find as the best solution a decrease in regolith packing density with increasing latitude. We also find that a variation of regolith grain size alone cannot explain the measurements. These predictions are valuable for planning future missions targeting higher latitudes and can be compared with future in situ measurements and returned samples. However, the fraction of sunlight that actually heats the regolith is quite unknown, especially at high latitudes. A variation of this fraction can explain the measured surface temperatures reasonably well even without a variation of the regolith properties with latitude.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉We developed a microphysical thermal model accounting for regolith grain size and volume filling factor〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉The best match between model and Lunar Reconnaissance Orbiter/Diviner data was achieved with a decrease in bulk density between 30° and 80° latitude〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉We also found a reasonable agreement between observed and modeled surface temperatures when varying the solar incidence dependent albedo〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: LRO project
    Description: https://doi.org/10.17189/WJ0S-W188
    Description: https://doi.org/10.5281/zenodo.8433837
    Description: https://doi.org/10.5281/zenodo.10781188
    Keywords: ddc:523 ; Moon ; regolith ; Diviner ; thermal modeling ; lunar
    Language: English
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  • 26
    Publication Date: 2024-05-23
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉The Ries impact structure (Germany) contains well‐preserved ejecta deposits consisting of melt‐free lithic breccia (Bunte Breccia) overlain by suevite. To test their emplacement conditions, we investigated the magnetic properties and microstructures of 26 polymict breccia clasts and a stratigraphic profile from the clasts into the suevite at the Aumühle quarry. Remanent magnetization directions of the Bunte Breccia clasts fall into two groups: those whose directions mostly lie parallel to the reversed field during impact carried mostly by magnetite, and those whose directions vary widely among each clast carried by titanohematite. Basement clasts containing titanohematite acquired a chemical remanent magnetization (CRM) during the ejection process and then rotated during turbulent deposition. Clasts of sedimentary rocks grew magnetite after turbulent deposition, with CRM directions lying parallel to the paleofield. Suevite holds a thermal remanent magnetization carried by magnetite, except for ∼12 cm from the contact with the Bunte Breccia, where hematite concentrations increase due to hydrothermal alteration. These observations lead us to propose a three‐stage model of (a) turbulent deposition of the melt‐free breccia with clast rotation 〈580°C, (b) deposition of the overlying suevite, which acted as a semi‐permeable barrier that confined hot (〈300°C) oxidizing fluids to the permeable breccia zone, and (c) prolonged hydrothermal activity producing further alteration which ended before the next geomagnetic reversal. Basement outcrops have significantly different magnetic properties than the Bunte Breccia basement clasts with similar lithology. Two basement blocks situated near the inner ring may have been thermally overprinted up to 550°C.〈/p〉
    Description: Plain Language Summary: The 26‐km‐diameter, ∼15‐million‐year‐old Ries meteorite impact structure in southern Germany is characterized by well‐preserved ejecta deposits expelled from the crater within seconds after the impact. These deposits consist of two main layers: melt‐free, lithic breccia (Bunte Breccia), overlain by melt‐bearing breccia (suevite). To understand the formation conditions of the ejecta deposits, we performed paleomagnetic and rock magnetic measurements and microstructural experiments on clasts within Bunte Breccia and on the overlying suevite at the Aumühle quarry. We found that clasts derived from crystalline basement materials experienced high pressures during the impact. These clasts had randomly oriented magnetization directions carried by titanohematite. In contrast, clasts derived from sedimentary rocks experienced only low pressures and had coherent magnetization directions oriented parallel to the reversed field during the impact that are carried by magnetite. Our findings can be interpreted by a three‐stage model that explains the thermal and structural formation of impact ejecta at the Ries impact structure.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉Randomly oriented paleomagnetic directions in basement clasts in ejecta deposits suggest turbulent emplacement〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉Bunte Breccia was chemically altered and locally heated by the overlying suevite, resulting in hydrothermal activity up to 300°C〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉Basement rocks near the inner ring may have experienced temperatures up to 550°C from cratering〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: https://earthref.org/MagIC/19984
    Keywords: ddc:622.153 ; Paleomagnetism ; remanent magnetization ; chemical remanence ; impact crater ; impact ejecta ; hydrothermal activity
    Language: English
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  • 27
    Publication Date: 2024-05-23
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Teleseismic back‐projection imaging has emerged as a powerful tool for understanding the rupture propagation of large earthquakes. However, its application often suffers from artifacts related to the receiver array geometry. We developed a teleseismic back‐projection technique that can accommodate data from multiple arrays. Combined processing of P and pP waveforms may further improve the resolution. The method is suitable for defining arrays ad‐hoc to achieve a good azimuthal distribution for most earthquakes. We present a catalog of short‐period rupture histories (0.5–2.0 Hz) for all earthquakes from 2010 to 2022 with 〈italic〉M〈/italic〉〈sub〉〈italic〉W〈/italic〉〈/sub〉 ≥ 7.5 and depth less than 200 km (56 events). The method provides automatic estimates of rupture length, directivity, speed, and aspect ratio, a proxy for rupture complexity. We obtained short‐period rupture length scaling relations that are in good agreement with previously published relations based on estimates of total slip. Rupture speeds were consistently in the sub‐Rayleigh regime for thrust and normal earthquakes, whereas a tenth of strike‐slip events propagated at supershear speeds. Many rupture histories exhibited complex behaviors, for example, rupture on conjugate faults, bilateral propagation, and dynamic triggering by a P wave. For megathrust earthquakes, ruptures encircling asperities were frequently observed, with downdip, updip, and balanced patterns. Although there is a preference for short‐period emissions to emanate from central and downdip parts of the megathrust, emissions updip of the main asperity are more frequent than suggested by earlier results.〈/p〉
    Description: Plain Language Summary: Back‐projection is an earthquake imaging method based on seismic waveforms recorded remotely at a group of seismometers (seismic array). Here, we develop a new approach to combine backprojections from multiple arrays and seismic waveforms and use it to derive a catalog of large earthquake rupture histories from 2010 to 2022, providing a map view of the high‐frequency radiation emitted along the fault. The method automatically estimates the earthquake rupture length, speed, directivity, and aspect ratio. Based on these estimates, we obtained scaling relations between the earthquake magnitude and rupture length that agree with classical relationships. We identified strike‐slip earthquakes propagating at supershear, that is, faster than the shear wave speed, the usual limit for self‐sustaining rupture propagation. We observed complex rupture behaviors, for example, multiple faults activated, bilateral ruptures, and triggering of the main phase of a rupture by a primary (P) wave from the earliest part of the rupture. For subduction earthquakes, high‐frequency emissions were often observed, forming a ring around the fault interface patches (asperities) where the main slip occurs. There was a preference for high‐frequency radiation to emanate from central and deeper parts of the subducting plate interface, but shallower emissions were more frequent than expected from previous literature.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉We provide a complete catalog of high‐frequency rupture histories for 〈italic〉M〈/italic〉 ≥ 7.5 events 2010–2022〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉We develop a semi‐automatic method for estimating rupture length, speed, directivity, and aspect ratio〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉Both encircling ruptures and emissions updip of slip asperities common in megathrust earthquakes〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: National Agency for Research and Development (ANID)
    Description: https://doi.org/10.5880/GFZ.2.4.2024.001
    Keywords: ddc:551.22 ; back‐projection ; megathrust earthquakes ; complex ruptures ; supershear ruptures ; scaling relations ; earthquake rupture catalog
    Language: English
    Type: doc-type:article
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  • 28
    Publication Date: 2024-05-30
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Mass transfer across the crust‐mantle boundary is a fundamental process governing planetary differentiation, the evolution of geochemical reservoirs and ore formation, controlled by physicochemical conditions at the crust‐mantle interface. In situ trace‐element, clinopyroxene 〈sup〉87〈/sup〉Sr/〈sup〉86〈/sup〉Sr and garnet Fe〈sup〉3+〈/sup〉/ΣFe of kimberlite‐borne eclogite xenoliths from the deep (∼50 km) crust‐mantle transition below the ca. 1.2–1.0 Ga Namaqua‐Natal Fold Belt (southwestern Kaapvaal craton margin) were determined to elucidate their origin and evolution, and to constrain the oxygen fugacity of this pivotal but largely inaccessible environment. Based on a garnet source signature (NMORB‐normalized Er/Lu > 1) in pristine “gabbroic” eclogites with pronounced positive Eu, Sr, and Pb anomalies, the suite is interpreted as originating as plagioclase‐rich cumulates in oceanic crust from melts generated beneath mature oceanic lithosphere, subsequently subducted during the Namaqua‐Natal orogeny. Enriched eclogites have higher measured 〈sup〉87〈/sup〉Sr/〈sup〉86〈/sup〉Sr in clinopyroxene (up to 0.7054) than gabbroic ones (up to 0.7036), and show increasing bulk‐rock Li, Be and Pb abundances with increasing δ〈sup〉18〈/sup〉O in clinopyroxene, and muted Eu‐Sr‐Pb anomalies. These systematics suggest interaction with a siliceous fluid sourced from seawater‐altered oceanic sediment in a subduction mélange setting. Garnet Fe〈sup〉3+〈/sup〉/ΣFe in deep crustal eclogites is extremely low (0.01–0.04, ±0.01 1〈italic〉σ〈/italic〉), as inherited from the plagioclase‐rich cumulate protolith, and owing to preferred partitioning into clinopyroxene at low temperatures (∼815–1000°C). Average maximum oxygen fugacities (∆logƒO〈sub〉2〈/sub〉(FMQ) = −3.1 ± 1.0 to −0.5 ± 0.7 relative to the Fayalite‐Magnetite‐Quartz buffer) are higher than in deeper‐seated on‐craton eclogite xenoliths, but mostly below sulfate stability, limiting the role of S〈sup〉6+〈/sup〉 species in oxidizing the mantle wedge.〈/p〉
    Description: Plain Language Summary: Subduction zones represent the main interface between Earth's surface and its deep interior. Metamorphic reactions during subduction cause fluid or melt loss from seawater‐altered oceanic crust and sediment, which enriches the overlying mantle, and possibly oxidizes it. This would explain why the mantle sources of subduction zone magmas appear to be more oxidized than in other tectonic settings. However, the details of the mass transfer in this deep environment are difficult to constrain because it is inaccessible. Using rare deep‐seated magmas (kimberlites) as probes of a ca. 1.2 billion year old southern African subduction zone, we investigated eclogite fragments that originated as subducted oceanic crust and were much later plucked from the wallrocks by the ascending magma. These eclogites show elemental and isotopic signatures of interaction with subducted sediments, pointing to mingling processes similar to those observed in modern subduction zones. We also estimated their oxygen fugacity, a measure of the chemical potential of oxygen. We find that sulfur, which has been implicated in mantle oxidation, would have only been stable in these rocks in its reduced form, making even seawater‐altered eclogites sinks rather than sources of oxygen, with implications for the transfer of sulfur‐loving metals across the mantle‐to‐crust‐boundary.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉Eclogite xenoliths sampling deep crust‐mantle transition below Namaqua‐Natal Fold Belt have plagioclase‐rich oceanic protoliths〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉Enriched xenoliths show signatures of interaction with siliceous, subducted sediment‐derived fluids under shallow fore‐arc conditions〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉Fe〈sup〉3+〈/sup〉‐based eclogite oxybarometry with oxygen fugacities below sulfate stability limits the role of S〈sup〉6+〈/sup〉 species in mantle wedge oxidation〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: Deutsche Forschungsgemeinschaft
    Description: https://doi.org/10.60520/IEDA/113077
    Keywords: ddc:552.4 ; kimberlite‐borne eclogite xenoliths ; crust‐mantle transition ; subduction zone processes ; redox budget ; metallogeny ; mantle wedge oxidation
    Language: English
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  • 29
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    Landesamt für Geologie und Bergbau Rheinland-Pfalz
    Publication Date: 2024-05-30
    Description: Ob Energiewende, die Gewinnung geothermischer Energie aus dem Boden, der Bau von unterirdischen Stromtrassen oder die Modellierung des Energiehaushalts der Erdoberfläche – die Kenntnisse der physikalisch-thermischen Eigenschaften des oberflächennahen Untergrundes sind von zentraler Bedeutung für zahlreiche Fragestellen der angewandten Bodenkunde. Böden als 3-Phasengemische aus Wasser, Luft und Festsubstanz können erhebliche Unterschiede und Differenzierungen bezüglich der thermischen Eigenschaften aufweisen. Neben dem Wasser- und Lufthaushalt sind Lagerungsdichte, Textur sowie die mineralogische Zusammensetzung entscheidende Einflussfaktoren. Auf Basis dieser Grundlagen wurden von verschiedenen Autoren Modellansätze entwickelt, um thermische Parameter bei unterschiedlichen Feuchtezuständen abzuleiten. Die meisten dieser Ansätze beruhen auf der Auswertung von repräsentativen Bodenproben, die ein möglichst breites Texturspektrum abbilden sollen. Die vorliegende Untersuchung verfolgt einen alternativen Ansatz. Durch Messungen im Routinebetrieb eines bodenphysikalischen Labors wurde ein umfangreicher Datensatz aufgebaut, der Auswertungen nach verschiedenen laboranalytischen sowie boden- und substratsystematischen Aspekten ermöglicht. Auf dieser breiten Datenbasis sollen die thermischen Eigenschaften von Böden bei definierten Randbedingungen noch genauer gefasst werden. Darüber hinaus sollen Grundlagen erarbeitet werden, die es ermöglichen, thermische Kennwerte über die Kenntnis einfacher Feldparameter möglichst präzise abzuschätzen.
    Description: research
    Keywords: ddc:631.436 ; Bodenphysik ; Wärmeleitfähigkeit ; Rheinland-Pfalz
    Language: German
    Type: doc-type:book , publishedVersion
    Format: 56
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  • 30
    Publication Date: 2024-06-07
    Description: Nach dem Streit um die Lieferung und den Besitz von Eisenstein zwischen Johannes, Abt des Klosters Grünhain, und Ernst II. von Schönburg, erließ Johannes mit Unterstützung von Kurfürst Johann Friedrich I. 1534 eine Bergordnung für den Eisensteinbergbau am Emmler und dem Hutstein.
    Description: source
    Keywords: Johannes Abt von Grünhain ; Kurfürst Johann Friedrich I. von Sachsen ; Ernst II. von Schönburg ; Kloster Grünhain ; Eisenerzbergbau
    Language: German
    Type: doc-type:book , updatedVersion
    Format: 6
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  • 31
    Publication Date: 2024-01-03
    Keywords: AGE; Antarctic Circumpolar Current; Clay; DEPTH, sediment/rock; Diatoms; Giant piston corer (Calypso); GPC-C; Grain size, Mastersizer S, Malvern Instrument Inc.; magnetic parameters; Marion Dufresne (1995); MD12-3401; MD128; mineralogic parameters; Silt; Summer sea surface temperature; SWAF
    Type: Dataset
    Format: text/tab-separated-values, 498 data points
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  • 32
    Publication Date: 2024-01-03
    Keywords: AGE; Anhysteretic susceptibility/magnetic susceptibility; Antarctic Circumpolar Current; Cryogenic magnetometer, 2G Enterprises; DEPTH, sediment/rock; Giant piston corer (Calypso); GPC-C; magnetic parameters; Magnetic susceptibility; Marion Dufresne (1995); MD12-3401; MD128; mineralogic parameters; Summer sea surface temperature; SWAF
    Type: Dataset
    Format: text/tab-separated-values, 320 data points
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  • 33
    Publication Date: 2024-01-03
    Keywords: AGE; Antarctic Circumpolar Current; calculated, 1 sigma; DEPTH, sediment/rock; Giant piston corer (Calypso); GPC-C; magnetic parameters; Marion Dufresne (1995); MD12-3401; MD128; mineralogic parameters; Reconstructed from the percentage of Neogloboquadrina pachyderma sinistral; Reconstructed from the percentage of planktic foraminifera; Sea surface temperature, summer; Sea surface temperature, summer, standard deviation; Summer sea surface temperature; SWAF
    Type: Dataset
    Format: text/tab-separated-values, 186 data points
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  • 34
    Publication Date: 2024-02-02
    Keywords: Azores; Azores Hot Vents; Center for Marine Environmental Sciences; Conductivity, thermal; Event label; heatflow; Heat flow; Heat-Flow probe; HF; Latitude of event; Longitude of event; M186; M186_12-1; M186_20-1; M186_26-1; M186_44-1; M186_47-1; M186_53-1; M186_66-1; M186_83-1; M186_85-1; MARUM; Meteor (1986); Sample code/label; Temperature gradient
    Type: Dataset
    Format: text/tab-separated-values, 280 data points
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  • 35
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    PANGAEA
    Publication Date: 2024-02-02
    Keywords: Azores; Azores Hot Vents; Center for Marine Environmental Sciences; Conductivity, thermal; Depth, relative; DEPTH, sediment/rock; Event label; heatflow; Heat flow probe; Heat-Flow probe; HF; Integrated thermal resistance; M186; M186_20-1; MARUM; Meteor (1986); Sample code/label; Station label; Temperature, in rock/sediment
    Type: Dataset
    Format: text/tab-separated-values, 1134 data points
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  • 36
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    PANGAEA
    Publication Date: 2024-02-02
    Keywords: Azores; Azores Hot Vents; Center for Marine Environmental Sciences; Conductivity, thermal; Depth, relative; DEPTH, sediment/rock; Event label; heatflow; Heat flow probe; Heat-Flow probe; HF; Integrated thermal resistance; M186; M186_12-1; MARUM; Meteor (1986); Sample code/label; Station label; Temperature, in rock/sediment
    Type: Dataset
    Format: text/tab-separated-values, 1512 data points
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  • 37
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    PANGAEA
    Publication Date: 2024-02-02
    Keywords: Azores; Azores Hot Vents; Center for Marine Environmental Sciences; Conductivity, thermal; Depth, relative; DEPTH, sediment/rock; Event label; heatflow; Heat flow probe; Heat-Flow probe; HF; Integrated thermal resistance; M186; M186_26-1; MARUM; Meteor (1986); Sample code/label; Station label; Temperature, in rock/sediment
    Type: Dataset
    Format: text/tab-separated-values, 891 data points
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  • 38
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    PANGAEA
    Publication Date: 2024-02-02
    Keywords: Azores; Azores Hot Vents; Center for Marine Environmental Sciences; Conductivity, thermal; Depth, relative; DEPTH, sediment/rock; Event label; heatflow; Heat flow probe; Heat-Flow probe; HF; Integrated thermal resistance; M186; M186_47-1; MARUM; Meteor (1986); Sample code/label; Station label; Temperature, in rock/sediment
    Type: Dataset
    Format: text/tab-separated-values, 946 data points
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  • 39
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    PANGAEA
    Publication Date: 2024-02-02
    Keywords: Azores; Azores Hot Vents; Center for Marine Environmental Sciences; Conductivity, thermal; Depth, relative; DEPTH, sediment/rock; Event label; heatflow; Heat flow probe; Heat-Flow probe; HF; Integrated thermal resistance; M186; M186_85-1; MARUM; Meteor (1986); Sample code/label; Station label; Temperature, in rock/sediment
    Type: Dataset
    Format: text/tab-separated-values, 1029 data points
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  • 40
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    PANGAEA
    Publication Date: 2024-02-02
    Keywords: Azores; Azores Hot Vents; Center for Marine Environmental Sciences; Conductivity, thermal; Depth, relative; DEPTH, sediment/rock; Event label; heatflow; Heat flow probe; Heat-Flow probe; HF; Integrated thermal resistance; M186; M186_83-1; MARUM; Meteor (1986); Sample code/label; Station label; Temperature, in rock/sediment
    Type: Dataset
    Format: text/tab-separated-values, 526 data points
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  • 41
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    PANGAEA
    Publication Date: 2024-02-02
    Keywords: Azores; Azores Hot Vents; Center for Marine Environmental Sciences; Conductivity, thermal; Depth, relative; DEPTH, sediment/rock; Event label; heatflow; Heat flow probe; Heat-Flow probe; HF; Integrated thermal resistance; M186; M186_66-1; MARUM; Meteor (1986); Sample code/label; Station label; Temperature, in rock/sediment
    Type: Dataset
    Format: text/tab-separated-values, 389 data points
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  • 42
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    PANGAEA
    Publication Date: 2024-02-02
    Keywords: Azores; Azores Hot Vents; Center for Marine Environmental Sciences; Conductivity, thermal; Depth, relative; DEPTH, sediment/rock; Event label; heatflow; Heat flow probe; Heat-Flow probe; HF; Integrated thermal resistance; M186; M186_53-1; MARUM; Meteor (1986); Sample code/label; Station label; Temperature, in rock/sediment
    Type: Dataset
    Format: text/tab-separated-values, 504 data points
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  • 43
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    PANGAEA
    Publication Date: 2024-02-02
    Keywords: Azores; Azores Hot Vents; Center for Marine Environmental Sciences; Conductivity, thermal; Depth, relative; DEPTH, sediment/rock; Event label; heatflow; Heat flow probe; Heat-Flow probe; HF; Integrated thermal resistance; M186; M186_53-1; MARUM; Meteor (1986); Sample code/label; Station label; Temperature, in rock/sediment
    Type: Dataset
    Format: text/tab-separated-values, 654 data points
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  • 44
    Publication Date: 2024-02-02
    Description: The data sets contains bulk organic data of sediment core GeoTü SL167. Total organic carbon and nitrogen measurements were carried out with an Euro EA3000 elemental analyser and δ15N measurements with a Thermo Scientific Flash EA1112 coupled to a Finnigan MAT 252 IRMS. Total organic carbon mass accumulation rates (TOC MAR) based on calculation using the organic carbon content and total mass accumulation rates. A description of the calculation of the total mass accumulations rates is given in Burdanowitz et al 2021. Gravity core GeoTü SL167, was retrieved at station no. 960 during R.V. METEOR cruise M74/1b in 2007 (Bohrmann et al., 2010) from the northwestern Arabian Sea off Oman, at 22°37.2'N, 59°41.5'E, 774 m water depth, core recovery 7.39 m. The sediment core was retrieved for the reconstruction of circulation and productivity changes in the eastern Mediterranean Sea during the late Quaternary with particular focus on changes in the Indian monsoon system.
    Keywords: Accumulation rate, total organic carbon per year; AGE; Age model; Arabian Sea; Calculated; CLICCS; Cluster of Excellence: Climate, Climatic Change, and Society; Denitrification; DEPTH, sediment/rock; Depth, sediment/rock, bottom/maximum; Depth, sediment/rock, top/minimum; Element analyzer, Thermo Scientific, Flash EA1112; coupled with a Finnigan MAT 252 IRMS; Gravity corer (Kiel type); M74/1b; M74/1b_960-1; Meteor (1986); n-alkanes; Oman Margin; OMZ; Quaternary; SL; SL 167; δ15N; δ15N, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 1846 data points
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  • 45
    Publication Date: 2024-02-02
    Description: The age model of sediment core GeoTü SL167 is based on 14C AMS measurements of planktonic foraminifera and is calibrated with the BACON v. 2.5.6 software for R (Blaauw & Christen, 2011) and a marine reservoir age of ΔR = 93 ± 61 years. The ΔR is based on the weighted mean of two regional marine reservoir corrections (Muscat) by Southon et al. (2002) using the marine calibration database (Reimer and Reimer, 2001, http://calib.org/marine/). Gravity core GeoTü SL167, was retrieved at station no. 960 during R.V. METEOR cruise M74/1b in 2007 (Bohrmann et al., 2010) from the northwestern Arabian Sea off Oman, at 22°37.2'N, 59°41.5'E, 774 m water depth, core recovery 7.39 m. The sediment core was retrieved for the reconstruction of circulation and productivity changes in the eastern Mediterranean Sea during the late Quaternary with particular focus on changes in the Indian monsoon system.
    Keywords: Age, 14C AMS; Age, 14C calibrated, BACON v. 2.5.6 (Blaauw and Christen, 2011); Age, dated; Age, dated standard deviation; Age model; Arabian Sea; Calendar age; Calendar age, maximum/old; Calendar age, minimum/young; CLICCS; Cluster of Excellence: Climate, Climatic Change, and Society; Denitrification; DEPTH, sediment/rock; Depth, sediment/rock, bottom/maximum; Depth, sediment/rock, top/minimum; Gravity corer (Kiel type); M74/1b; M74/1b_960-1; Meteor (1986); n-alkanes; Oman Margin; OMZ; Quaternary; SL; SL 167
    Type: Dataset
    Format: text/tab-separated-values, 147 data points
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  • 46
    Publication Date: 2024-02-02
    Description: The onset of the first sustained Antarctic glaciation at the Eocene-Oligocene Transition (~34 Ma; EOT) was marked by several changes in calcareous nannofossils coinciding with long-term cooling and modifications in the sea-surface water structure. Here, we combined a high-resolution calcareous nannofossil assemblage data (%) with bulk geochemical data from IODP Site U1509 (New Caledonia Trough, Tasman Sea) in order to give an overview of the paleoclimatic and palaeoceanographic evolution of the study area.
    Keywords: 371-U1509A; Calcareous nannofossils; Calcium carbonate; DEPTH, sediment/rock; DSDP/ODP/IODP sample designation; Eocene-Oligocene Transition.; Exp371; Integrated Ocean Drilling Program / International Ocean Discovery Program; IODP; IODP Depth Scale Terminology; Isotope ratio mass spectrometry; Joides Resolution; Sample code/label; Tasman Frontier Subduction Initiation and Paleogene Climate; Tasman Sea; δ13C, carbonate; δ18O, carbonate
    Type: Dataset
    Format: text/tab-separated-values, 732 data points
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  • 47
    Publication Date: 2024-02-01
    Description: Marine heat flow data from RV Meteor cruise M186. The GEOMAR project name is Azores Hot Vents. We used the 6 m Bremen heat probe with 21 channels @ 0.26 m spacing.
    Keywords: Azores; Center for Marine Environmental Sciences; heatflow; MARUM
    Type: Dataset
    Format: application/zip, 10 datasets
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  • 48
    Publication Date: 2024-03-01
    Description: This data set contains airborne gravity data across central Dronning Maud Land, East Antarctica, acquired during the austral summer of 2009/2010 and within the project 'West-East Gondwana Amalgamation and its Separation' (WEGAS). The data span the offshore Astrid Ridge, and parts of the Nivl and Lazarev ice shelves. The survey was conducted using a ZLS Ultrasys Lacoste & Romberg Air/Sea gravimeter S56 installed into - and operated with - the research aircraft Polar 5. Base readings were performed with a handheld gravity meter at the base station Novolazarevskaja and in Cape Town. A ground speed of 130 knots and a time-domain filter of 220 s leads to a spatial resolution of around 7 km. The average crossover error after bias adjustment is 4.2 mGal. When citing this data set, please also cite the associated manuscript: Eisermann, H., Eagles, G. & Jokat, W. Coastal bathymetry in central Dronning Maud Land controls ice shelf stability. Sci Rep 14, 1367 (2024). https://doi.org/10.1038/s41598-024-51882-2.
    Keywords: AC; airborne gravity; Aircraft; Antarctica; Antarctica, East; Astrid Ridge; DATE/TIME; Event label; Free-air gravity anomaly; Gravity; Height; LATITUDE; Lazarev Ice Shelf; Line; LONGITUDE; Nivl Ice Shelf; PGM17 (NGA's Preliminary Geopotential Model 2017); POLAR 5; WEGAS_2009/10; WEGAS_2009/10_02; WEGAS_2009/10_03; WEGAS_2009/10_04; WEGAS_2009/10_05; WEGAS_2009/10_06; WEGAS_2009/10_07; WEGAS_2009/10_08; WEGAS_2009/10_09; WEGAS_2009/10_10; WEGAS_2009/10_11; WEGAS_2009/10_12; WEGAS_2009/10_13; WEGAS_2009/10_14; WEGAS_2009/10_16; WEGAS_2009/10_17; WEGAS_2009/10_18; WEGAS_2009/10_19; WEGAS_2009/10_20; WEGAS_2009/10_21; WEGAS offshore
    Type: Dataset
    Format: text/tab-separated-values, 128088 data points
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  • 49
    Publication Date: 2024-03-01
    Description: Attached data comprise a bathymetric model of central Dronning Maud Land, including the seabed beneath the Nivl Ice Shelf and the Lazarev Ice Shelf, as well as the offshore Astrid Ridge and adjacent parts of the Riiser-Larsen Sea. Here, this model is embedded within the larger Antarctic-wide bathymetric compilation IBCSOV2 (Dorschel et al., 2022). This is an addition to the stand-alone bathymetric model here: https://doi.org/10.1594/PANGAEA.961492. The embedded model gives seabed depths relative to WGS84 at a resolution of 2.5 km. It is generated by complementing existing topographic data sets - such as seismic data, ice penetrating radar data, and shipborne hydroacoustic data - with the inversion of airborne gravity data towards bathymetry. The airborne gravity data used for the inversion consist of data acquired during aerogeophysical campaigns VISA from the early 2000s and WEGAS from the austral summer of 2009/2010. When citing this model, please also cite the associated manuscript: Eisermann, H., Eagles, G. & Jokat, W. Coastal bathymetry in central Dronning Maud Land controls ice shelf stability. Sci Rep 14, 1367 (2024). https://doi.org/10.1038/s41598-024-51882-2.
    Keywords: Antarctica; Bathymetry; BathymetryModel_cDronningMaudLan; Bed elevation; Coordinate, x, relative; Coordinate, y, relative; Dronning Maud Land; Dronning Maud Land, Antarctica; gravity inversion; LATITUDE; Lazarev Ice Shelf; LONGITUDE; Model; Nivl Ice Shelf; water column
    Type: Dataset
    Format: text/tab-separated-values, 206742 data points
    Location Call Number Expected Availability
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  • 50
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Ice mass balance; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Quality flag, position; Sea Ice Physics @ AWI; snow depth; Snow height; solar radiation; Tilt angle, X; Tilt angle, Y
    Type: Dataset
    Format: text/tab-separated-values, 29044 data points
    Location Call Number Expected Availability
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  • 51
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Ice mass balance; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Quality flag, position; Sea Ice Physics @ AWI; snow depth; solar radiation; Temperature, difference
    Type: Dataset
    Format: text/tab-separated-values, 89452 data points
    Location Call Number Expected Availability
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  • 52
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Ice mass balance; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Quality flag, position; Sea Ice Physics @ AWI; snow depth; solar radiation; Temperature, difference
    Type: Dataset
    Format: text/tab-separated-values, 89452 data points
    Location Call Number Expected Availability
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  • 53
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Ice mass balance; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Quality flag, position; Sea Ice Physics @ AWI; snow depth; solar radiation; Temperature, difference
    Type: Dataset
    Format: text/tab-separated-values, 89452 data points
    Location Call Number Expected Availability
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  • 54
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Ice mass balance; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Quality flag, position; Sea Ice Physics @ AWI; snow depth; solar radiation; Temperature, difference
    Type: Dataset
    Format: text/tab-separated-values, 36366 data points
    Location Call Number Expected Availability
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  • 55
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Ice mass balance; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Quality flag, position; Sea Ice Physics @ AWI; snow depth; solar radiation; Temperature, difference
    Type: Dataset
    Format: text/tab-separated-values, 53713 data points
    Location Call Number Expected Availability
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  • 56
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Ice mass balance; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Quality flag, position; Sea Ice Physics @ AWI; snow depth; solar radiation; Temperature, technical
    Type: Dataset
    Format: text/tab-separated-values, 253099 data points
    Location Call Number Expected Availability
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  • 57
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; Calculated; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Ice mass balance; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Quality flag, sun elevation; Sea Ice Physics @ AWI; snow depth; solar radiation; Transmittance; Transmittance, photosynthetically active; Transmittance at 320 nm; Transmittance at 321 nm; Transmittance at 322 nm; Transmittance at 323 nm; Transmittance at 324 nm; Transmittance at 325 nm; Transmittance at 326 nm; Transmittance at 327 nm; Transmittance at 328 nm; Transmittance at 329 nm; Transmittance at 330 nm; Transmittance at 331 nm; Transmittance at 332 nm; Transmittance at 333 nm; Transmittance at 334 nm; Transmittance at 335 nm; Transmittance at 336 nm; Transmittance at 337 nm; Transmittance at 338 nm; Transmittance at 339 nm; Transmittance at 340 nm; Transmittance at 341 nm; Transmittance at 342 nm; Transmittance at 343 nm; Transmittance at 344 nm; Transmittance at 345 nm; Transmittance at 346 nm; Transmittance at 347 nm; Transmittance at 348 nm; Transmittance at 349 nm; Transmittance at 350 nm; Transmittance at 351 nm; Transmittance at 352 nm; Transmittance at 353 nm; Transmittance at 354 nm; Transmittance at 355 nm; Transmittance at 356 nm; Transmittance at 357 nm; Transmittance at 358 nm; Transmittance at 359 nm; Transmittance at 360 nm; Transmittance at 361 nm; Transmittance at 362 nm; Transmittance at 363 nm; Transmittance at 364 nm; Transmittance at 365 nm; Transmittance at 366 nm; Transmittance at 367 nm; Transmittance at 368 nm; Transmittance at 369 nm; Transmittance at 370 nm; Transmittance at 371 nm; Transmittance at 372 nm; Transmittance at 373 nm; Transmittance at 374 nm; Transmittance at 375 nm; Transmittance at 376 nm; Transmittance at 377 nm; Transmittance at 378 nm; Transmittance at 379 nm; Transmittance at 380 nm; Transmittance at 381 nm; Transmittance at 382 nm; Transmittance at 383 nm; Transmittance at 384 nm; Transmittance at 385 nm; Transmittance at 386 nm; Transmittance at 387 nm; Transmittance at 388 nm; Transmittance at 389 nm; Transmittance at 390 nm; Transmittance at 391 nm; Transmittance at 392 nm; Transmittance at 393 nm; Transmittance at 394 nm; Transmittance at 395 nm; Transmittance at 396 nm; Transmittance at 397 nm; Transmittance at 398 nm; Transmittance at 399 nm; Transmittance at 400 nm; Transmittance at 401 nm; Transmittance at 402 nm; Transmittance at 403 nm; Transmittance at 404 nm; Transmittance at 405 nm; Transmittance at 406 nm; Transmittance at 407 nm; Transmittance at 408 nm; Transmittance at 409 nm; Transmittance at 410 nm; Transmittance at 411 nm; Transmittance at 412 nm; Transmittance at 413 nm; Transmittance at 414 nm; Transmittance at 415 nm; Transmittance at 416 nm; Transmittance at 417 nm; Transmittance at 418 nm; Transmittance at 419 nm; Transmittance at 420 nm; Transmittance at 421 nm; Transmittance at 422 nm; Transmittance at 423 nm; Transmittance at 424 nm; Transmittance at 425 nm; Transmittance at 426 nm; Transmittance at 427 nm; Transmittance at 428 nm; Transmittance at 429 nm; Transmittance at 430 nm; Transmittance at 431 nm; Transmittance at 432 nm; Transmittance at 433 nm; Transmittance at 434 nm; Transmittance at 435 nm; Transmittance at 436 nm; Transmittance at 437 nm; Transmittance at 438 nm; Transmittance at 439 nm; Transmittance at 440 nm; Transmittance at 441 nm; Transmittance at 442 nm; Transmittance at 443 nm; Transmittance at 444 nm; Transmittance at 445 nm; Transmittance at 446 nm; Transmittance at 447 nm; Transmittance at 448 nm; Transmittance at 449 nm; Transmittance at 450 nm; Transmittance at 451 nm; Transmittance at 452 nm; Transmittance at 453 nm; Transmittance at 454 nm; Transmittance at 455 nm; Transmittance at 456 nm; Transmittance at 457 nm; Transmittance at 458 nm; Transmittance at 459 nm; Transmittance at 460 nm; Transmittance at 461 nm; Transmittance at 462 nm; Transmittance at 463 nm; Transmittance at 464 nm; Transmittance at 465 nm; Transmittance at 466 nm; Transmittance at 467 nm; Transmittance at 468 nm; Transmittance at 469 nm; Transmittance at 470 nm; Transmittance at 471 nm; Transmittance at 472 nm; Transmittance at 473 nm; Transmittance at 474 nm; Transmittance at 475 nm; Transmittance at 476 nm; Transmittance at 477 nm; Transmittance at 478 nm; Transmittance at 479 nm; Transmittance at 480 nm; Transmittance at 481 nm; Transmittance at 482 nm; Transmittance at 483 nm; Transmittance at 484 nm; Transmittance at 485 nm; Transmittance at 486 nm; Transmittance at 487 nm; Transmittance at 488 nm; Transmittance at 489 nm; Transmittance at 490 nm; Transmittance at 491 nm; Transmittance at 492 nm; Transmittance at 493 nm; Transmittance at 494 nm; Transmittance at 495 nm; Transmittance at 496 nm; Transmittance at 497 nm; Transmittance at 498 nm; Transmittance at 499 nm; Transmittance at 500 nm; Transmittance at 501 nm; Transmittance at 502 nm; Transmittance at 503 nm; Transmittance at 504 nm; Transmittance at 505 nm; Transmittance at 506 nm; Transmittance at 507 nm; Transmittance at 508 nm; Transmittance at 509 nm; Transmittance at 510 nm; Transmittance at 511 nm; Transmittance at 512 nm; Transmittance at 513 nm; Transmittance at 514 nm; Transmittance at 515 nm; Transmittance at 516 nm; Transmittance at 517 nm; Transmittance at 518 nm; Transmittance at 519 nm; Transmittance at 520 nm; Transmittance at 521 nm; Transmittance at 522 nm; Transmittance at 523 nm; Transmittance at 524 nm; Transmittance at 525 nm; Transmittance at 526 nm; Transmittance at 527 nm; Transmittance at 528 nm; Transmittance at 529 nm; Transmittance at 530 nm; Transmittance at 531 nm; Transmittance at 532 nm; Transmittance at 533 nm; Transmittance at 534 nm; Transmittance at 535 nm; Transmittance at 536 nm; Transmittance at 537 nm; Transmittance at 538 nm; Transmittance at 539 nm; Transmittance at 540 nm; Transmittance at 541 nm; Transmittance at 542 nm; Transmittance at 543 nm; Transmittance at 544 nm; Transmittance at 545 nm; Transmittance at 546 nm; Transmittance at 547 nm; Transmittance at 548 nm; Transmittance at 549 nm; Transmittance at 550 nm; Transmittance at 551 nm; Transmittance at 552 nm; Transmittance at 553 nm; Transmittance at 554 nm; Transmittance at 555 nm; Transmittance at 556 nm; Transmittance at 557 nm; Transmittance at 558 nm; Transmittance at 559 nm; Transmittance at 560 nm; Transmittance at 561 nm; Transmittance at 562 nm; Transmittance at 563 nm; Transmittance at 564 nm; Transmittance at 565 nm; Transmittance at 566 nm; Transmittance at 567 nm; Transmittance at 568 nm; Transmittance at 569 nm; Transmittance at 570 nm; Transmittance at 571 nm; Transmittance at 572 nm; Transmittance at 573 nm; Transmittance at 574 nm; Transmittance at 575 nm; Transmittance at 576 nm; Transmittance at 577 nm; Transmittance at 578 nm; Transmittance at 579 nm; Transmittance at 580 nm; Transmittance at 581 nm; Transmittance at 582 nm; Transmittance at 583 nm; Transmittance at 584 nm; Transmittance at 585 nm; Transmittance at 586 nm; Transmittance at 587 nm; Transmittance at 588 nm; Transmittance at 589 nm; Transmittance at 590 nm; Transmittance at 591 nm; Transmittance at 592 nm; Transmittance at 593 nm; Transmittance at 594 nm; Transmittance at 595 nm; Transmittance at 596 nm; Transmittance at 597 nm; Transmittance at 598 nm; Transmittance at 599 nm; Transmittance at 600 nm; Transmittance at 601 nm; Transmittance at 602 nm; Transmittance at 603 nm; Transmittance at 604 nm; Transmittance at 605 nm; Transmittance at 606 nm; Transmittance at 607 nm; Transmittance at 608 nm; Transmittance at 609 nm; Transmittance at 610 nm; Transmittance at 611 nm; Transmittance at 612 nm; Transmittance at 613 nm; Transmittance at 614 nm; Transmittance at 615 nm; Transmittance
    Type: Dataset
    Format: text/tab-separated-values, 738492 data points
    Location Call Number Expected Availability
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  • 58
    Publication Date: 2024-03-05
    Keywords: 138-846B; 138-846C; AGE; Alkenone; Aluminium oxide; Barium sulfate; Calcium carbonate; Calibrated after Weltje & Tjallingi (2008); Date/Time of event; Depth, composite; DRILL; Drilling/drill rig; Eastern Equatorial Pacific; Event label; Iron oxide, Fe2O3; Joides Resolution; Latitude of event; Leg138; Longitude of event; Manganese oxide; ODP Site 846; Sample code/label; Sea surface temperature; Silicon dioxide; South Pacific Ocean; Titanium dioxide
    Type: Dataset
    Format: text/tab-separated-values, 75384 data points
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  • 59
    Publication Date: 2024-03-05
    Keywords: 138-846; A205402GC; A210804; Alkenone; Argo; BC; Box corer; COMPCORE; Composite Core; Core; CORE; core top; DEPTH, sediment/rock; DWBG-143; DWBG-144; Eastern Equatorial Pacific; Equatorial East Pacific; Event label; GC; Gravity corer; Hakuho-Maru; HY06; Joides Resolution; KH-03-1; Knorr; KNR073-04-003; KNR073-04-008; KNR073-04-009; KNR073-04-010; KNR182-9; KNR182-9-MC15; KNR195-05-005-10-GGC; KNR195-05-14-35-GGC; KNR195-05-GGC005-10; KNR195-05-GGC14-35; KNR195-5; KNR195-5-MC12; KNR195-5-MC18; KNR195-5-MC22; KNR195-5-MC25; KNR195-5-MC33; KNR195-5-MC34; KNR733P; KNR73-4GC-008; KNR73-4GC-009; KNR73-4GC-010; Latitude of event; Leg138; Literature based; Longitude of event; ME0005A; ME0005A-25MC5; Melville; MODIS; MUC; MultiCorer; NEMO; P6702-11G; P6702-52G; Pacific Ocean; PC; Piston corer; PLDS-068BX; PLDS-070BX; PLDS-072BX; PLDS-074BX; PLDS-077BX; PLDS-090BX; PLDS-3; Pleiades; RC11; RC1112; RC11-238; RC13; RC13-108; Reference/source; Robert Conrad; Sample ID; SCAN; SCAN-095G; Sea surface temperature; South Pacific Ocean; SST; Thomas Washington; TR163-22; TR163-31; Uniform resource locator/link to reference; V19; V19-28; V19-30; V21; V21-30; Vema; VNTR01; VNTR01-10GC; VNTR01-13GC; VNTR01-9PC; Y69-71P; YALOC69; Yaquina
    Type: Dataset
    Format: text/tab-separated-values, 210 data points
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  • 60
    Publication Date: 2024-03-05
    Keywords: 138-846; A205402GC; A210804; Alkenone; Argo; BC; Box corer; Calculated; Chlorophyll, logarithm; Chlorophyll total; COMPCORE; Composite Core; Core; CORE; core top; DEPTH, sediment/rock; DWBG-143; DWBG-144; Eastern Equatorial Pacific; Equatorial East Pacific; Event label; GC; Gravity corer; Hakuho-Maru; HY06; Joides Resolution; KH-03-1; Knorr; KNR073-04-003; KNR073-04-008; KNR073-04-009; KNR073-04-010; KNR182-9; KNR182-9-MC15; KNR195-05-005-10-GGC; KNR195-05-14-35-GGC; KNR195-05-GGC005-10; KNR195-05-GGC14-35; KNR195-5; KNR195-5-MC12; KNR195-5-MC18; KNR195-5-MC22; KNR195-5-MC25; KNR195-5-MC33; KNR195-5-MC34; KNR733P; KNR73-4GC-008; KNR73-4GC-009; KNR73-4GC-010; Latitude of event; Leg138; Literature based; Longitude of event; ME0005A; ME0005A-25MC5; Melville; MODIS; MUC; MultiCorer; NEMO; P6702-11G; P6702-52G; Pacific Ocean; PC; Piston corer; PLDS-068BX; PLDS-070BX; PLDS-072BX; PLDS-074BX; PLDS-077BX; PLDS-090BX; PLDS-3; Pleiades; RC11; RC1112; RC11-238; RC13; RC13-108; Reference/source; Robert Conrad; Sample ID; SCAN; SCAN-095G; Sea surface temperature; South Pacific Ocean; SST; Thomas Washington; TR163-22; TR163-31; Uniform resource locator/link to reference; V19; V19-28; V19-30; V21; V21-30; Vema; VNTR01; VNTR01-10GC; VNTR01-13GC; VNTR01-9PC; Y69-71P; YALOC69; Yaquina
    Type: Dataset
    Format: text/tab-separated-values, 210 data points
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  • 61
    Publication Date: 2024-03-05
    Keywords: 138-846; A205402GC; A210804; Alkenone; Alkenone, C37 per unit sediment mass; Argo; BC; Box corer; COMPCORE; Composite Core; Core; CORE; core top; DEPTH, sediment/rock; DWBG-143; DWBG-144; Eastern Equatorial Pacific; Equatorial East Pacific; Event label; GC; Gravity corer; Hakuho-Maru; HY06; Joides Resolution; KH-03-1; Knorr; KNR073-04-003; KNR073-04-008; KNR073-04-009; KNR073-04-010; KNR182-9; KNR182-9-MC15; KNR195-05-005-10-GGC; KNR195-05-14-35-GGC; KNR195-05-GGC005-10; KNR195-05-GGC14-35; KNR195-5; KNR195-5-MC12; KNR195-5-MC18; KNR195-5-MC22; KNR195-5-MC25; KNR195-5-MC33; KNR195-5-MC34; KNR733P; KNR73-4GC-008; KNR73-4GC-009; KNR73-4GC-010; Latitude of event; Leg138; Literature based; Longitude of event; ME0005A; ME0005A-25MC5; Melville; MODIS; MUC; MultiCorer; NEMO; P6702-11G; P6702-52G; Pacific Ocean; PC; Piston corer; PLDS-068BX; PLDS-070BX; PLDS-072BX; PLDS-074BX; PLDS-077BX; PLDS-090BX; PLDS-3; Pleiades; RC11; RC1112; RC11-238; RC13; RC13-108; Reference/source; Robert Conrad; Sample ID; SCAN; SCAN-095G; Sea surface temperature; South Pacific Ocean; SST; Thomas Washington; TR163-22; TR163-31; Uniform resource locator/link to reference; V19; V19-28; V19-30; V21; V21-30; Vema; VNTR01; VNTR01-10GC; VNTR01-13GC; VNTR01-9PC; Y69-71P; YALOC69; Yaquina
    Type: Dataset
    Format: text/tab-separated-values, 147 data points
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  • 62
    Publication Date: 2024-03-05
    Keywords: 138-846; A205402GC; A210804; Alkenone; Argo; BC; Box corer; Coccolithaceae, biomass; COMPCORE; Composite Core; Core; CORE; core top; DEPTH, sediment/rock; DWBG-143; DWBG-144; Eastern Equatorial Pacific; Equatorial East Pacific; Event label; GC; Gravity corer; Hakuho-Maru; HY06; Joides Resolution; KH-03-1; Knorr; KNR073-04-003; KNR073-04-008; KNR073-04-009; KNR073-04-010; KNR182-9; KNR182-9-MC15; KNR195-05-005-10-GGC; KNR195-05-14-35-GGC; KNR195-05-GGC005-10; KNR195-05-GGC14-35; KNR195-5; KNR195-5-MC12; KNR195-5-MC18; KNR195-5-MC22; KNR195-5-MC25; KNR195-5-MC33; KNR195-5-MC34; KNR733P; KNR73-4GC-008; KNR73-4GC-009; KNR73-4GC-010; Latitude of event; Leg138; Literature based; Longitude of event; ME0005A; ME0005A-25MC5; Melville; MODIS; MUC; MultiCorer; NEMO; P6702-11G; P6702-52G; Pacific Ocean; PC; Piston corer; PLDS-068BX; PLDS-070BX; PLDS-072BX; PLDS-074BX; PLDS-077BX; PLDS-090BX; PLDS-3; Pleiades; RC11; RC1112; RC11-238; RC13; RC13-108; Reference/source; Robert Conrad; Sample ID; SCAN; SCAN-095G; Sea surface temperature; South Pacific Ocean; SST; Thomas Washington; TR163-22; TR163-31; Uniform resource locator/link to reference; V19; V19-28; V19-30; V21; V21-30; Vema; VNTR01; VNTR01-10GC; VNTR01-13GC; VNTR01-9PC; Y69-71P; YALOC69; Yaquina
    Type: Dataset
    Format: text/tab-separated-values, 166 data points
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  • 63
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Ice mass balance; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; Pressure, water; PS122/1_1-167, 2019R8; Sea Ice Physics @ AWI; snow depth; solar radiation; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 108915 data points
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  • 64
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Ice mass balance; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Quality flag, position; Sea Ice Physics @ AWI; snow depth; solar radiation; Temperature, difference
    Type: Dataset
    Format: text/tab-separated-values, 90079 data points
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  • 65
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Ice mass balance; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Quality flag, position; Sea Ice Physics @ AWI; snow depth; solar radiation; Temperature, difference
    Type: Dataset
    Format: text/tab-separated-values, 53713 data points
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  • 66
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Ice mass balance; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Quality flag, position; Sea Ice Physics @ AWI; snow depth; solar radiation; Temperature, difference
    Type: Dataset
    Format: text/tab-separated-values, 36366 data points
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  • 67
    Publication Date: 2024-03-05
    Keywords: 138-846; According to Herbert et al. (2021); Accumulation rate, alkenone C37; AGE; Alkenone; Alkenone, C37, logarithm; Calculated; COMPCORE; Composite Core; Eastern Equatorial Pacific; Joides Resolution; Leg138; ODP Site 846; Sea surface temperature; South Pacific Ocean
    Type: Dataset
    Format: text/tab-separated-values, 1056 data points
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  • 68
    Publication Date: 2024-03-05
    Keywords: 138-849; According to Herbert et al. (2021); Accumulation rate, alkenone C37; AGE; Alkenone; Alkenone, C37, logarithm; Calculated; COMPCORE; Composite Core; Eastern Equatorial Pacific; Joides Resolution; Leg138; North Pacific Ocean; ODP Site 846; Sea surface temperature
    Type: Dataset
    Format: text/tab-separated-values, 388 data points
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  • 69
    Publication Date: 2024-03-05
    Keywords: 321-U1338; According to Herbert et al. (2021); Accumulation rate, alkenone C37; AGE; Alkenone; Alkenone, C37, logarithm; Calculated; COMPCORE; Composite Core; Eastern Equatorial Pacific; Exp321; Joides Resolution; ODP Site 846; Pacific Equatorial Age Transect II / Juan de Fuca; Sea surface temperature
    Type: Dataset
    Format: text/tab-separated-values, 422 data points
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  • 70
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    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 22236 data points
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  • 71
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 257782 data points
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  • 72
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 25033 data points
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  • 73
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 23254 data points
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  • 74
    Publication Date: 2024-02-29
    Description: Dinoflagellate cysts have been determined in sediments of core DP30PC on a resolution of 1 sample per 2.5 mm core depth (representing approximately 3 year) and 119.65 - 180.4 cm core depth. These data form the basis of high temporal resolution temperature and precipitation reconstructions for Roman times between about 200 BCE and 600 CE (ca. 205 BCE - 605 CE).
    Keywords: 64PE297; Age; Ataxiodinium choane; Bitectatodinium tepikiense; Center for Marine Environmental Sciences; Counting, dinoflagellate cysts; DEPTH, sediment/rock; Dinoflagellate cyst, other; Dinoflagellate cyst, warm water/cold water, ratio; Dinoflagellate cyst reworked; Discharge index; DP30PC; elements; Impagidinium aculeatum; Impagidinium paradoxum; Impagidinium patulum; Impagidinium plicatum; Impagidinium sphaericum; Impagidinium strialatum; Lingulodinium polyedrum; MARUM; Mediterranean; Nematosphaeropsis labyrinthus; Operculodinium israelianum; PC; Pelagia; Piston corer; Polysphaeridium zoharyi; Pseudoschizea spp.; Pyxidinopsis reticulata; Roman Climate Optimum; Spiniferites elongatus; Spiniferites mirabilis; Spiniferites ramosus; Tectatodinium pellitum; Temperature, water; Tuberculodinium vancampoae; volcanic glass shards
    Type: Dataset
    Format: text/tab-separated-values, 6092 data points
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  • 75
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 27270 data points
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  • 76
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 29012 data points
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  • 77
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Horizontal visibility; HYGRO; Hygrometer; Monitoring station; MONS; Pressure, atmospheric; SYO; Syowa; Temperature, air; Thermometer; Visibility sensor; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 267840 data points
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  • 78
    facet.materialart.
    Unknown
    PANGAEA
    In:  Japan Meteorological Agency, Tokyo
    Publication Date: 2024-02-29
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; Cosmonauts Sea; DATE/TIME; Dew/frost point; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, MEISEI, RS11G; SYO; Syowa; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 24245 data points
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  • 79
    Publication Date: 2024-02-28
    Keywords: AGE; Age, 14C calibrated; age depth model; Aluminium; Beckman Coulter Laser diffraction particle size analyzer LS 13 320; Calcium; Color, a*; Color, b*; Color, L*, lightness; COR1404; COR1404-003PC; Coriolis II; Depth, reconstructed; DEPTH, sediment/rock; elemental geochemistry; Grain size, mean; Grain size data; Gulf of San Jorge; Gulf of San Jorge, Argentina; Iron; magnetic susceptibility; Magnetic susceptibility; Manganese; MARGES; Multi-Sensor Core Logger (MSCL), GEOTEK; Olympus InnovX Delta portable XRF; Patagonia; PC; Percentile 10; Percentile 50; Percentile 90; Piston corer; Potassium; Rubidium; Silicon; Size fraction 〉 2 mm, gravel; Spectrophotometer Minolta CM-260; Strontium; Titanium; Zirconium
    Type: Dataset
    Format: text/tab-separated-values, 6167 data points
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  • 80
    Publication Date: 2024-02-28
    Keywords: age depth model; Aluminium; Beckman Coulter Laser diffraction particle size analyzer LS 13 320; Calcium; Color, a*; Color, b*; Color, L*, lightness; COR1404; COR1404-001PC; Coriolis II; DEPTH, sediment/rock; elemental geochemistry; Grain size, mean; Grain size data; Gulf of San Jorge; Gulf of San Jorge, Argentina; Iron; magnetic susceptibility; Magnetic susceptibility; Manganese; MARGES; Multi-Sensor Core Logger (MSCL), GEOTEK; Olympus InnovX Delta portable XRF; Patagonia; PC; Percentile 10; Percentile 50; Percentile 90; Piston corer; Potassium; Rubidium; Silicon; Size fraction 〉 2 mm, gravel; Spectrophotometer Minolta CM-260; Strontium; Titanium; Zirconium
    Type: Dataset
    Format: text/tab-separated-values, 1440 data points
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  • 81
    Publication Date: 2024-02-28
    Keywords: AGE; Age, 14C calibrated; age depth model; Aluminium; Beckman Coulter Laser diffraction particle size analyzer LS 13 320; Calcium; Color, a*; Color, b*; Color, L*, lightness; COR1404; COR1404-006PC; Coriolis II; Depth, reconstructed; DEPTH, sediment/rock; elemental geochemistry; Grain size, mean; Grain size data; Gulf of San Jorge; Gulf of San Jorge, Argentina; Iron; magnetic susceptibility; Magnetic susceptibility; Manganese; MARGES; Multi-Sensor Core Logger (MSCL), GEOTEK; Olympus InnovX Delta portable XRF; Patagonia; PC; Percentile 10; Percentile 50; Percentile 90; Piston corer; Potassium; Rubidium; Silicon; Size fraction 〉 2 mm, gravel; Spectrophotometer Minolta CM-260; Strontium; Titanium; Zirconium
    Type: Dataset
    Format: text/tab-separated-values, 5540 data points
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  • 82
    Publication Date: 2024-02-28
    Keywords: AGE; Age, 14C calibrated; age depth model; Aluminium; Beckman Coulter Laser diffraction particle size analyzer LS 13 320; Calcium; Color, a*; Color, b*; Color, L*, lightness; COR1404; COR1404-008PC; Coriolis II; Depth, reconstructed; DEPTH, sediment/rock; elemental geochemistry; Grain size, mean; Grain size data; Gulf of San Jorge; Gulf of San Jorge, Argentina; Iron; magnetic susceptibility; Magnetic susceptibility; Manganese; MARGES; Multi-Sensor Core Logger (MSCL), GEOTEK; Olympus InnovX Delta portable XRF; Patagonia; PC; Percentile 10; Percentile 50; Percentile 90; Piston corer; Potassium; Rubidium; Silicon; Size fraction 〉 2 mm, gravel; Spectrophotometer Minolta CM-260; Strontium; Titanium; Zirconium
    Type: Dataset
    Format: text/tab-separated-values, 4023 data points
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  • 83
    Publication Date: 2024-03-12
    Keywords: Aluminium oxide; Ardmore; Area/locality; Barium oxide; Barr_Creek; Calcium oxide; Cerium; Chromium(III) oxide; Depth, description; DEPTH, sediment/rock; DTREE; Duchess; Dysprosium; Erbium; Europium; Event label; Gadolinium; Georgina Basin; Hole; Holmium; Iron oxide, Fe2O3; Lanthanum; Laser Ablation; LATITUDE; Lily_Creek; LONGITUDE; Loss on ignition; Lutetium; Magnesium oxide; Manganese oxide; Neodymium; Paradise_North; Paradise_South; Phosphate_Hill; Phosphorite; Phosphorus pentoxide; Potassium oxide; Praseodymium; Rare-earth elements; ROCK; Rock sample; Samarium; Sample code/label; Sherrin_Creek; Silicon dioxide; Sodium oxide; Strontium oxide; Terbium; Thorium; Thulium; Titanium dioxide; Total; Uranium; Whole rock geochemistry; Ytterbium; Yttrium; Zirconium
    Type: Dataset
    Format: text/tab-separated-values, 1327 data points
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  • 84
    Publication Date: 2024-03-12
    Keywords: Aluminium; Aluminium oxide; Barium; Barium oxide; Calcium; Calcium oxide; Cerium; Cerium oxid; Chlorine; Date of determination; Electron micro probe analyser (EMPA); Fluorine; Gadolinium; Gadolinium oxide; Georgina Basin; Iron; Iron oxide, Fe2O3; Lanthanum; Lanthanum oxide; Laser Ablation; LATITUDE; LONGITUDE; Magnesium; Magnesium oxide; Manganese; Manganese oxide; Mineral name; Neodymium; Neodymium oxid; Oxygen; Phosphorite; Phosphorus; Phosphorus pentoxide; Sample ID; Silicon; Silicon dioxide; Site; Sodium; Sodium oxide; Strontium; Strontium oxide; Sulfur; Sulfur trioxide; Total; Whole rock geochemistry; Yttrium; Yttrium oxide
    Type: Dataset
    Format: text/tab-separated-values, 1764 data points
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  • 85
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-12
    Description: We continuously measured aerosol size distributions in the range between 18 nm and 820 nm in 64 bit per decade resolution by means of a Scanning Mobility Particle Sizer (SMPS, TSI, i.e. a Series 3080 Electrostatic Classifier equipped with a Differential Mobility Analyzer DMA 3081). The measurements were conducted at the Air Chemistry Observatory (SPUSO) at Neumayer III Station (Antarctica) between 4 August 2023 and 31 December 2023. The data are based on an original 10-minute temporal resolution, submitted as 60-minute averages. Aerosol size distribution measurements are part of the air chemistry long-term observations at Neumayer III. Details about the instrument can be found under "resources" of the corresponding metadata link: https://hdl.handle.net/10013/sensor.81ece554-068a-4c6e-8de5-1ef1944c0156
    Keywords: aerosol; Air chemistry observatory; Air Chemistry Observatory; Atmospheric Chemistry @ AWI; AWI_AC; AWI_Glac; DATE/TIME; Date/time end; Dronning Maud Land, Antarctica; Glaciology @ AWI; HEIGHT above ground; Log-normal particle size distribution, normalized concentration at particle diameter 101.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 105.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 109.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 113.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 117.6 nm; Log-normal particle size distribution, normalized concentration at particle diameter 121.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 126.3 nm; Log-normal particle size distribution, normalized concentration at particle diameter 131 nm; Log-normal particle size distribution, normalized concentration at particle diameter 135.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 140.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 145.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 151.2 nm; Log-normal particle size distribution, normalized concentration at particle diameter 156.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 162.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 168.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 174.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 18.1 nm; Log-normal particle size distribution, normalized concentration at particle diameter 18.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 181.1 nm; Log-normal particle size distribution, normalized concentration at particle diameter 187.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 19.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 194.6 nm; Log-normal particle size distribution, normalized concentration at particle diameter 20.2 nm; Log-normal particle size distribution, normalized concentration at particle diameter 20.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 201.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 209.1 nm; Log-normal particle size distribution, normalized concentration at particle diameter 21.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 216.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 22.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 224.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 23.3 nm; Log-normal particle size distribution, normalized concentration at particle diameter 232.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 24.1 nm; Log-normal particle size distribution, normalized concentration at particle diameter 241.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 25.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 250.3 nm; Log-normal particle size distribution, normalized concentration at particle diameter 259.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 25 nm; Log-normal particle size distribution, normalized concentration at particle diameter 26.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 269 nm; Log-normal particle size distribution, normalized concentration at particle diameter 27.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 278.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 28.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 289 nm; Log-normal particle size distribution, normalized concentration at particle diameter 299.6 nm; Log-normal particle size distribution, normalized concentration at particle diameter 30 nm; Log-normal particle size distribution, normalized concentration at particle diameter 31.1 nm; Log-normal particle size distribution, normalized concentration at particle diameter 310.6 nm; Log-normal particle size distribution, normalized concentration at particle diameter 32.2 nm; Log-normal particle size distribution, normalized concentration at particle diameter 322 nm; Log-normal particle size distribution, normalized concentration at particle diameter 33.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 333.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 34.6 nm; Log-normal particle size distribution, normalized concentration at particle diameter 346 nm; Log-normal particle size distribution, normalized concentration at particle diameter 35.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 358.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 37.2 nm; Log-normal particle size distribution, normalized concentration at particle diameter 371.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 38.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 385.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 399.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 40 nm; Log-normal particle size distribution, normalized concentration at particle diameter 41.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 414.2 nm; Log-normal particle size distribution, normalized concentration at particle diameter 42.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 429.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 44.5 nm; Log-normal particle size distribution, normalized concentration at particle diameter 445.1 nm; Log-normal particle size distribution, normalized concentration at particle diameter 46.1 nm; Log-normal particle size distribution, normalized concentration at particle diameter 461.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 47.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 478.3 nm; Log-normal particle size distribution, normalized concentration at particle diameter 49.6 nm; Log-normal particle size distribution, normalized concentration at particle diameter 495.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 51.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 514 nm; Log-normal particle size distribution, normalized concentration at particle diameter 53.3 nm; Log-normal particle size distribution, normalized concentration at particle diameter 532.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 55.2 nm; Log-normal particle size distribution, normalized concentration at particle diameter 552.3 nm; Log-normal particle size distribution, normalized concentration at particle diameter 57.3 nm; Log-normal particle size distribution, normalized concentration at particle diameter 572.5 nm; Log-normal particle size distribution, normalized
    Type: Dataset
    Format: text/tab-separated-values, 385097 data points
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  • 86
    Publication Date: 2024-03-12
    Keywords: Aluminium; Aluminium oxide; Antimony; Ardmore; Area/locality; Arsenic; Barium; Barr_Creek; Beryllium; Bismuth; Boron; Cadmium; Caesium; Calcium; Calcium oxide; Cerium; Chromium; Cobalt; Copper; DTREE; Duchess; Dysprosium; Erbium; Europium; Gadolinium; Georgina Basin; Hafnium; Holmium; Inductively coupled plasma - mass spectrometry (ICP-MS); Iron; Iron oxide, Fe2O3; Lanthanum; Laser Ablation; LATITUDE; Lead-208; Lily_Creek; Lithium; Lithium borate fusion; acid digestion; LONGITUDE; Lutetium; Magnesium; Magnesium oxide; Manganese; Manganese oxide; Molybdenum; Neodymium; Nickel; Niobium; Paradise_North; Paradise_South; Phosphate_Hill; Phosphorite; Phosphorus; Phosphorus pentoxide; Potassium; Potassium oxide; Praseodymium; Rhenium; ROCK; Rock sample; Rock type; Rubidium; Samarium; Sample ID; Scandium; Sherrin_Creek; Silicon; Silicon dioxide; Sodium; Sodium oxide; Strontium; Tantalum; Tellurium; Terbium; Thallium; Thorium; Thulium; Tin; Titanium; Titanium dioxide; Total; Uranium; Vanadium; Whole rock geochemistry; Ytterbium; Yttrium; Zinc; Zirconium
    Type: Dataset
    Format: text/tab-separated-values, 837 data points
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  • 87
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-09
    Description: We operate a multi angle absorption photometer MAAP (Model 5012, Thermo Electron Corp.). which is in operation since March 2006 ongoing. This instrument measures atmospheric light absorption by aerosol (mainly caused by black carbon, BC). To this end, ambient aerosol was sampled on a glass filter tape. The measured absorption coefficients abs(637) refer to a wavelength of 637 nm. Raw data were originally sampled in one-minute resolution. Finally, hourly averaged MAAP data are presented here. We also provide BC concentrations (ng/m³) derived from the absorption coefficients using the specific BC attenuation cross section (QBC) of 6.6 m²/g.
    Keywords: aerosol; Aerosol absorption at 637 nm; AIRCHEM; Air chemistry observatory; Atmospheric chemistry; Atmospheric Chemistry @ AWI; AWI_AC; Black carbon, aerosol; DATE/TIME; Dronning Maud Land, Antarctica; Duration; HEIGHT above ground; Multi angle absorption spectrometer MAAP5012; Neumayer_based; Neumayer_SPUSO; NEUMAYER III; Spuso; SPUSO
    Type: Dataset
    Format: text/tab-separated-values, 26274 data points
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  • 88
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-09
    Description: We continuously measured aerosol size distributions in the range between 90 nm and 5000 nm in 64 bit resolution with an optical particle sizer (TSI LAS3340). The measurements were conducted at the Air Chemistry Observatory (SPUSO) at Neumayer III Station (Antarctica) between 1 January 2023 and 10 July 2023. The data rely on an original 10-minute temporal resolution and are finally submitted as 60-minute averages. Aerosol size distribution measurements are part of the air chemistry long-term observations at Neumayer III. Details about the instrument can be found under "resources" of the corresponding metadata link: https://hdl.handle.net/10013/sensor.5d9a9253-e118-4744-be3a-05f31551314a.
    Keywords: aerosol; Air chemistry observatory; Air Chemistry Observatory; Atmospheric Chemistry @ AWI; AWI_AC; AWI_Glac; DATE/TIME; Date/time end; Dronning Maud Land, Antarctica; Glaciology @ AWI; HEIGHT above ground; las3340; Laser Aerosol Spectrometer TSI LAS3340; Log-normal particle size distribution, normalized concentration at particle diameter 1008.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 105.29 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1074.15 nm; Log-normal particle size distribution, normalized concentration at particle diameter 112.11 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1143.74 nm; Log-normal particle size distribution, normalized concentration at particle diameter 119.38 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1217.84 nm; Log-normal particle size distribution, normalized concentration at particle diameter 127.11 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1296.74 nm; Log-normal particle size distribution, normalized concentration at particle diameter 135.34 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1380.74 nm; Log-normal particle size distribution, normalized concentration at particle diameter 144.11 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1470.19 nm; Log-normal particle size distribution, normalized concentration at particle diameter 153.45 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1565.43 nm; Log-normal particle size distribution, normalized concentration at particle diameter 163.39 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1666.85 nm; Log-normal particle size distribution, normalized concentration at particle diameter 173.97 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1774.83 nm; Log-normal particle size distribution, normalized concentration at particle diameter 185.24 nm; Log-normal particle size distribution, normalized concentration at particle diameter 1889.81 nm; Log-normal particle size distribution, normalized concentration at particle diameter 197.25 nm; Log-normal particle size distribution, normalized concentration at particle diameter 2012.24 nm; Log-normal particle size distribution, normalized concentration at particle diameter 210.03 nm; Log-normal particle size distribution, normalized concentration at particle diameter 2142.6 nm; Log-normal particle size distribution, normalized concentration at particle diameter 223.63 nm; Log-normal particle size distribution, normalized concentration at particle diameter 2281.41 nm; Log-normal particle size distribution, normalized concentration at particle diameter 238.12 nm; Log-normal particle size distribution, normalized concentration at particle diameter 2429.21 nm; Log-normal particle size distribution, normalized concentration at particle diameter 253.55 nm; Log-normal particle size distribution, normalized concentration at particle diameter 2586.58 nm; Log-normal particle size distribution, normalized concentration at particle diameter 269.97 nm; Log-normal particle size distribution, normalized concentration at particle diameter 2754.15 nm; Log-normal particle size distribution, normalized concentration at particle diameter 287.46 nm; Log-normal particle size distribution, normalized concentration at particle diameter 2932.57 nm; Log-normal particle size distribution, normalized concentration at particle diameter 306.08 nm; Log-normal particle size distribution, normalized concentration at particle diameter 3122.55 nm; Log-normal particle size distribution, normalized concentration at particle diameter 325.91 nm; Log-normal particle size distribution, normalized concentration at particle diameter 3324.84 nm; Log-normal particle size distribution, normalized concentration at particle diameter 347.02 nm; Log-normal particle size distribution, normalized concentration at particle diameter 3540.24 nm; Log-normal particle size distribution, normalized concentration at particle diameter 369.51 nm; Log-normal particle size distribution, normalized concentration at particle diameter 3769.59 nm; Log-normal particle size distribution, normalized concentration at particle diameter 393.45 nm; Log-normal particle size distribution, normalized concentration at particle diameter 4013.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 418.93 nm; Log-normal particle size distribution, normalized concentration at particle diameter 4273.82 nm; Log-normal particle size distribution, normalized concentration at particle diameter 446.08 nm; Log-normal particle size distribution, normalized concentration at particle diameter 4550.7 nm; Log-normal particle size distribution, normalized concentration at particle diameter 474.98 nm; Log-normal particle size distribution, normalized concentration at particle diameter 4845.51 nm; Log-normal particle size distribution, normalized concentration at particle diameter 505.75 nm; Log-normal particle size distribution, normalized concentration at particle diameter 538.51 nm; Log-normal particle size distribution, normalized concentration at particle diameter 573.4 nm; Log-normal particle size distribution, normalized concentration at particle diameter 610.54 nm; Log-normal particle size distribution, normalized concentration at particle diameter 650.09 nm; Log-normal particle size distribution, normalized concentration at particle diameter 692.21 nm; Log-normal particle size distribution, normalized concentration at particle diameter 737.05 nm; Log-normal particle size distribution, normalized concentration at particle diameter 784.8 nm; Log-normal particle size distribution, normalized concentration at particle diameter 835.64 nm; Log-normal particle size distribution, normalized concentration at particle diameter 889.78 nm; Log-normal particle size distribution, normalized concentration at particle diameter 92.87 nm; Log-normal particle size distribution, normalized concentration at particle diameter 947.42 nm; Log-normal particle size distribution, normalized concentration at particle diameter 98.89 nm; Neumayer; Neumayer_based; Neumayer_SPUSO; NEUMAYER III; size distribution; Spuso; SPUSO; Time in minutes
    Type: Dataset
    Format: text/tab-separated-values, 300234 data points
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  • 89
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-12
    Description: We operate a 7-wavelength aethalometer (Model AE33, Magee Scientific) which is in operation since 23 January 2019 ongoing. The Aethalometer model AE33 collects aerosol particles continuously by drawing the aerosol-laden air stream through a spot on the filter tape. It analyzes the aerosol by measuring the transmission of light through one portion of the filter tape containing the sample, versus the transmission through an unloaded portion of the filter tape acting as a reference area. This analysis is done at seven optical wavelengths spanning the range from the near-infrared to the near-ultraviolet. The Aethalometer calculates the instantaneous concentration of optically-absorbing aerosols from the rate of change of the attenuation of light transmitted through the particle-laden filter.
    Keywords: aerosol; Aerosol absorption at 370 nm; Aerosol absorption at 470 nm; Aerosol absorption at 520 nm; Aerosol absorption at 590 nm; Aerosol absorption at 660 nm; Aerosol absorption at 880 nm; Aerosol absorption at 950 nm; aerosol absorption coefficient; Aethalometer, AE33, Magee Scientific; Air chemistry observatory; Air Chemistry Observatory; Atmospheric Chemistry @ AWI; AWI_AC; DATE/TIME; Dronning Maud Land, Antarctica; Duration; HEIGHT above ground; Neumayer_based; Neumayer_SPUSO; NEUMAYER III; Neumayer Station; Spuso; SPUSO
    Type: Dataset
    Format: text/tab-separated-values, 131400 data points
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  • 90
    Publication Date: 2024-03-05
    Description: Multiproxy analysis (including magnetic susceptibility, diffuse spectral reflectance, elemental geochemistry and grain size) of five sediment piston cores (COR1404-001PC, COR1404-003PC, COR1404-006PC, COR1404-008PC and COR1404-011PC) in order to characterize the evolution of sedimentary environments and depositional history of the Gulf of San Jorge (Patagonia, Argentina) since the Last Glacial Maximum. The data were collected on board the R/V Coriolis II during the MARGES (Marine Geology of the Gulf of San Jorge) expedition (January 29 to March 4, 2014) as part of the PROMESSe (PROgrama Multidisciplinario para el Estudio del ecosistema y la geología marina del golfo San Jorge y las costas de las provincias de Chubut y Santa Cruz) project. Color reflectance, pXRF and magnetic susceptibility were performed at 1-cm intervals on freshly split core sections using a GEOTEK Multi-Sensor Core Logger. Prior to grain size analysis, the five piston cores were evenly sampled every 8 cm with a refined sampling at 4-cm intervals for basal sections of cores COR1404-003PC, COR1404-006PC and COR1404-008PC. Grain size analysis of sediment samples was carried out on the detrital fraction using a Beckman Coulter LS 13 320 particle size analyser. The age-depth models were generated with radiocarbon ages calibrated using the software CALIB version 7.1, the Marine13 calibration curve and a marine regional reservoir correction (ΔR) of 0. The “best fit” linearly interpolated age-depth models were constructed with the Bayesian statistical approach of the BACON v2.2 package of the R software.
    Keywords: age depth model; elemental geochemistry; Grain size data; Gulf of San Jorge; magnetic susceptibility; Patagonia
    Type: Dataset
    Format: application/zip, 5 datasets
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  • 91
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; drift; FDOM; Ice mass balance; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Sea Ice Physics @ AWI; snow depth; solar radiation
    Type: Dataset
    Format: application/zip, 19 datasets
    Location Call Number Expected Availability
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  • 92
    Publication Date: 2024-03-05
    Description: Vegetated coastal ecosystems have been increasingly recognized for their capacity to sequester organic carbon in their soils and sediments under the term blue carbon. The vegetation of these habitats shows specific adaptations to severe abiotic soil conditions, particularly, waterlogging and salinity, and supports therefore ecosystem functioning and services. Wadden Sea salt marshes in Schleswig-Holstein (Germany) have been utilized for high density sheep grazing over centuries. At the beginning of the 1990s, in many parts of salt marshes livestock densities were reduced and the maintenance of the anthropogenic drainage system was ceased. In 2012, 17 years after the change of land utilization, the contents, densities, and accumulation rates of surface soil carbon were investigated at 50 sampling positions with different elevations along eight transects in Wadden Sea mainland salt marshes at Hamburger Hallig, Schleswig-Holstein, Germany, under different livestock grazing regimes (ungrazed, moderately grazed, intensively grazed). Surface soil was collected in 150 permanent plots (2 m * 2 m) at 50 sampling positions, covering a salt marsh area of 1050 ha. The carbon contents, pH, and bulk density were determined from dried soil. The elevations of the 150 permanent plots were measured and annual vertical accretion rates were calculated from 17 years sedimentation monitoring. This study was supported by the BASSIA project (Biodiversity, management, and ecosystem functions of salt marshes in the Wadden Sea National Park of Schleswig-Holstein), funded by the Bauer-Hollmann Foundation and Universität Hamburg.
    Keywords: Agrostis stolonifera, cover; Armeria maritima, cover; Artemisia maritima, cover; Aster tripolium, cover; Atriplex littoralis, cover; Atriplex portulacoides, cover; Atriplex prostrata, cover; blue carbon; Calculated; Climate change; DATE/TIME; Density, dry bulk; Depth, soil, maximum; Distance; ELEVATION; Elymus athericus, cover; Elymus repens, cover; Festuca rubra, cover; Glaux maritima, cover; inorganic and organic carbon stock; Inorganic carbon, soil; Juncus gerardii, cover; Limonium vulgare, cover; Livestock density; Multi parameter analyser, Eijkelkamp, 18.28; Optical levelling instrument; Organic carbon, soil; pH; Plantago coronopus, cover; Plantago maritima, cover; Plot of land; Potentilla anserina, cover; Puccinellia maritima, cover; Salicornia europaea, cover; Sample position; Sea level rise; Soil corer; Sonchus asper, cover; Sonchus sp., cover; Spartina anglica, cover; Spergularia maritima, cover; SSC_2012_HH-SH-G; Suaeda maritima, cover; tidal wetland; TMAP Wadden Sea Vegetation Database (Stock 2012); Total organic carbon (TOC) analyzer, Elementar, Liqui-TOC; coupled with extension module, Elementar, soliTIC; Triglochin maritima, cover; Vegetation, cover; Vegetation type; Vertical accretion rate, annual mean; Wadden Sea, Germany
    Type: Dataset
    Format: text/tab-separated-values, 5300 data points
    Location Call Number Expected Availability
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  • 93
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; Calculated; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Ice mass balance; Irradiance, upward, reflected at sea ice surface; Irradiance, upward, reflected at sea ice surface, photosythetically active; Irradiance, upward, reflected at sea ice surface, photosythetically active, absolute; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Quality flag, sun elevation; Sea Ice Physics @ AWI; snow depth; solar radiation; Spectral irradiance, upward, reflected at sea ice surface at 320 nm; Spectral irradiance, upward, reflected at sea ice surface at 321 nm; Spectral irradiance, upward, reflected at sea ice surface at 322 nm; Spectral irradiance, upward, reflected at sea ice surface at 323 nm; Spectral irradiance, upward, reflected at sea ice surface at 324 nm; Spectral irradiance, upward, reflected at sea ice surface at 325 nm; Spectral irradiance, upward, reflected at sea ice surface at 326 nm; Spectral irradiance, upward, reflected at sea ice surface at 327 nm; Spectral irradiance, upward, reflected at sea ice surface at 328 nm; Spectral irradiance, upward, reflected at sea ice surface at 329 nm; Spectral irradiance, upward, reflected at sea ice surface at 330 nm; Spectral irradiance, upward, reflected at sea ice surface at 331 nm; Spectral irradiance, upward, reflected at sea ice surface at 332 nm; Spectral irradiance, upward, reflected at sea ice surface at 333 nm; Spectral irradiance, upward, reflected at sea ice surface at 334 nm; Spectral irradiance, upward, reflected at sea ice surface at 335 nm; Spectral irradiance, upward, reflected at sea ice surface at 336 nm; Spectral irradiance, upward, reflected at sea ice surface at 337 nm; Spectral irradiance, upward, reflected at sea ice surface at 338 nm; Spectral irradiance, upward, reflected at sea ice surface at 339 nm; Spectral irradiance, upward, reflected at sea ice surface at 340 nm; Spectral irradiance, upward, reflected at sea ice surface at 341 nm; Spectral irradiance, upward, reflected at sea ice surface at 342 nm; Spectral irradiance, upward, reflected at sea ice surface at 343 nm; Spectral irradiance, upward, reflected at sea ice surface at 344 nm; Spectral irradiance, upward, reflected at sea ice surface at 345 nm; Spectral irradiance, upward, reflected at sea ice surface at 346 nm; Spectral irradiance, upward, reflected at sea ice surface at 347 nm; Spectral irradiance, upward, reflected at sea ice surface at 348 nm; Spectral irradiance, upward, reflected at sea ice surface at 349 nm; Spectral irradiance, upward, reflected at sea ice surface at 350 nm; Spectral irradiance, upward, reflected at sea ice surface at 351 nm; Spectral irradiance, upward, reflected at sea ice surface at 352 nm; Spectral irradiance, upward, reflected at sea ice surface at 353 nm; Spectral irradiance, upward, reflected at sea ice surface at 354 nm; Spectral irradiance, upward, reflected at sea ice surface at 355 nm; Spectral irradiance, upward, reflected at sea ice surface at 356 nm; Spectral irradiance, upward, reflected at sea ice surface at 357 nm; Spectral irradiance, upward, reflected at sea ice surface at 358 nm; Spectral irradiance, upward, reflected at sea ice surface at 359 nm; Spectral irradiance, upward, reflected at sea ice surface at 360 nm; Spectral irradiance, upward, reflected at sea ice surface at 361 nm; Spectral irradiance, upward, reflected at sea ice surface at 362 nm; Spectral irradiance, upward, reflected at sea ice surface at 363 nm; Spectral irradiance, upward, reflected at sea ice surface at 364 nm; Spectral irradiance, upward, reflected at sea ice surface at 365 nm; Spectral irradiance, upward, reflected at sea ice surface at 366 nm; Spectral irradiance, upward, reflected at sea ice surface at 367 nm; Spectral irradiance, upward, reflected at sea ice surface at 368 nm; Spectral irradiance, upward, reflected at sea ice surface at 369 nm; Spectral irradiance, upward, reflected at sea ice surface at 370 nm; Spectral irradiance, upward, reflected at sea ice surface at 371 nm; Spectral irradiance, upward, reflected at sea ice surface at 372 nm; Spectral irradiance, upward, reflected at sea ice surface at 373 nm; Spectral irradiance, upward, reflected at sea ice surface at 374 nm; Spectral irradiance, upward, reflected at sea ice surface at 375 nm; Spectral irradiance, upward, reflected at sea ice surface at 376 nm; Spectral irradiance, upward, reflected at sea ice surface at 377 nm; Spectral irradiance, upward, reflected at sea ice surface at 378 nm; Spectral irradiance, upward, reflected at sea ice surface at 379 nm; Spectral irradiance, upward, reflected at sea ice surface at 380 nm; Spectral irradiance, upward, reflected at sea ice surface at 381 nm; Spectral irradiance, upward, reflected at sea ice surface at 382 nm; Spectral irradiance, upward, reflected at sea ice surface at 383 nm; Spectral irradiance, upward, reflected at sea ice surface at 384 nm; Spectral irradiance, upward, reflected at sea ice surface at 385 nm; Spectral irradiance, upward, reflected at sea ice surface at 386 nm; Spectral irradiance, upward, reflected at sea ice surface at 387 nm; Spectral irradiance, upward, reflected at sea ice surface at 388 nm; Spectral irradiance, upward, reflected at sea ice surface at 389 nm; Spectral irradiance, upward, reflected at sea ice surface at 390 nm; Spectral irradiance, upward, reflected at sea ice surface at 391 nm; Spectral irradiance, upward, reflected at sea ice surface at 392 nm; Spectral irradiance, upward, reflected at sea ice surface at 393 nm; Spectral irradiance, upward, reflected at sea ice surface at 394 nm; Spectral irradiance, upward, reflected at sea ice surface at 395 nm; Spectral irradiance, upward, reflected at sea ice surface at 396 nm; Spectral irradiance, upward, reflected at sea ice surface at 397 nm; Spectral irradiance, upward, reflected at sea ice surface at 398 nm; Spectral irradiance, upward, reflected at sea ice surface at 399 nm; Spectral irradiance, upward, reflected at sea ice surface at 400 nm; Spectral irradiance, upward, reflected at sea ice surface at 401 nm; Spectral irradiance, upward, reflected at sea ice surface at 402 nm; Spectral irradiance, upward, reflected at sea ice surface at 403 nm; Spectral irradiance, upward, reflected at sea ice surface at 404 nm; Spectral irradiance, upward, reflected at sea ice surface at 405 nm; Spectral irradiance, upward, reflected at sea ice surface at 406 nm; Spectral irradiance, upward, reflected at sea ice surface at 407 nm; Spectral irradiance, upward, reflected at sea ice surface at 408 nm; Spectral irradiance, upward, reflected at sea ice surface at 409 nm; Spectral irradiance, upward, reflected at sea ice surface at 410 nm; Spectral irradiance, upward, reflected at sea ice surface at 411 nm; Spectral irradiance, upward, reflected at sea ice surface at 412 nm; Spectral irradiance, upward, reflected at sea ice surface at 413 nm; Spectral irradiance, upward, reflected at sea ice surface at 414 nm; Spectral irradiance, upward, reflected at sea ice surface at 415 nm; Spectral irradiance, upward, reflected at sea ice surface at 416 nm; Spectral irradiance, upward, reflected at sea ice surface at 417 nm; Spectral irradiance, upward, reflected at sea ice surface at 418 nm; Spectral irradiance, upward, reflected at sea ice surface at 419 nm; Spectral irradiance, upward, reflected at sea ice surface at 420 nm; Spectral irradiance, upward, reflected at sea ice surface at 421 nm; Spectral irradiance, upward, reflected at sea ice surface at 422 nm; Spectral irradiance, upward, reflected at sea ice surface at 423 nm; Spectral irradiance, upward, reflected at sea ice surface at 424 nm; Spectral
    Type: Dataset
    Format: text/tab-separated-values, 955680 data points
    Location Call Number Expected Availability
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  • 94
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorologisches Observatorium Potsdam
    Publication Date: 2024-03-02
    Keywords: Anemometer; BARO; Barometer; Baseline Surface Radiation Network; BSRN; Code; DATE/TIME; Dew/frost point; Germany; HYGRO; Hygrometer; LIN; Lindenberg; Monitoring station; MONS; Past weather1; Past weather2; Present weather; Pressure, atmospheric; Station pressure; Temperature, air; Thermometer; Total cloud amount; Visual observation; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 6265 data points
    Location Call Number Expected Availability
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  • 95
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorologisches Observatorium Potsdam
    Publication Date: 2024-03-02
    Keywords: Baseline Surface Radiation Network; BSRN; Cloud base height; DATE/TIME; Germany; LIN; Lindenberg; Monitoring station; MONS
    Type: Dataset
    Format: text/tab-separated-values, 3422 data points
    Location Call Number Expected Availability
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  • 96
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorologisches Observatorium Potsdam
    Publication Date: 2024-03-02
    Keywords: ALTITUDE; Baseline Surface Radiation Network; BSRN; DATE/TIME; Dew/frost point; Germany; LIN; Lindenberg; Monitoring station; MONS; Pressure, at given altitude; Radiosonde, Vaisala, RS41; Temperature, air; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 782989 data points
    Location Call Number Expected Availability
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  • 97
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Albedo, fraction; Albedo, photosynthetically active; Albedo at 320 nm; Albedo at 321 nm; Albedo at 322 nm; Albedo at 323 nm; Albedo at 324 nm; Albedo at 325 nm; Albedo at 326 nm; Albedo at 327 nm; Albedo at 328 nm; Albedo at 329 nm; Albedo at 330 nm; Albedo at 331 nm; Albedo at 332 nm; Albedo at 333 nm; Albedo at 334 nm; Albedo at 335 nm; Albedo at 336 nm; Albedo at 337 nm; Albedo at 338 nm; Albedo at 339 nm; Albedo at 340 nm; Albedo at 341 nm; Albedo at 342 nm; Albedo at 343 nm; Albedo at 344 nm; Albedo at 345 nm; Albedo at 346 nm; Albedo at 347 nm; Albedo at 348 nm; Albedo at 349 nm; Albedo at 350 nm; Albedo at 351 nm; Albedo at 352 nm; Albedo at 353 nm; Albedo at 354 nm; Albedo at 355 nm; Albedo at 356 nm; Albedo at 357 nm; Albedo at 358 nm; Albedo at 359 nm; Albedo at 360 nm; Albedo at 361 nm; Albedo at 362 nm; Albedo at 363 nm; Albedo at 364 nm; Albedo at 365 nm; Albedo at 366 nm; Albedo at 367 nm; Albedo at 368 nm; Albedo at 369 nm; Albedo at 370 nm; Albedo at 371 nm; Albedo at 372 nm; Albedo at 373 nm; Albedo at 374 nm; Albedo at 375 nm; Albedo at 376 nm; Albedo at 377 nm; Albedo at 378 nm; Albedo at 379 nm; Albedo at 380 nm; Albedo at 381 nm; Albedo at 382 nm; Albedo at 383 nm; Albedo at 384 nm; Albedo at 385 nm; Albedo at 386 nm; Albedo at 387 nm; Albedo at 388 nm; Albedo at 389 nm; Albedo at 390 nm; Albedo at 391 nm; Albedo at 392 nm; Albedo at 393 nm; Albedo at 394 nm; Albedo at 395 nm; Albedo at 396 nm; Albedo at 397 nm; Albedo at 398 nm; Albedo at 399 nm; Albedo at 400 nm; Albedo at 401 nm; Albedo at 402 nm; Albedo at 403 nm; Albedo at 404 nm; Albedo at 405 nm; Albedo at 406 nm; Albedo at 407 nm; Albedo at 408 nm; Albedo at 409 nm; Albedo at 410 nm; Albedo at 411 nm; Albedo at 412 nm; Albedo at 413 nm; Albedo at 414 nm; Albedo at 415 nm; Albedo at 416 nm; Albedo at 417 nm; Albedo at 418 nm; Albedo at 419 nm; Albedo at 420 nm; Albedo at 421 nm; Albedo at 422 nm; Albedo at 423 nm; Albedo at 424 nm; Albedo at 425 nm; Albedo at 426 nm; Albedo at 427 nm; Albedo at 428 nm; Albedo at 429 nm; Albedo at 430 nm; Albedo at 431 nm; Albedo at 432 nm; Albedo at 433 nm; Albedo at 434 nm; Albedo at 435 nm; Albedo at 436 nm; Albedo at 437 nm; Albedo at 438 nm; Albedo at 439 nm; Albedo at 440 nm; Albedo at 441 nm; Albedo at 442 nm; Albedo at 443 nm; Albedo at 444 nm; Albedo at 445 nm; Albedo at 446 nm; Albedo at 447 nm; Albedo at 448 nm; Albedo at 449 nm; Albedo at 450 nm; Albedo at 451 nm; Albedo at 452 nm; Albedo at 453 nm; Albedo at 454 nm; Albedo at 455 nm; Albedo at 456 nm; Albedo at 457 nm; Albedo at 458 nm; Albedo at 459 nm; Albedo at 460 nm; Albedo at 461 nm; Albedo at 462 nm; Albedo at 463 nm; Albedo at 464 nm; Albedo at 465 nm; Albedo at 466 nm; Albedo at 467 nm; Albedo at 468 nm; Albedo at 469 nm; Albedo at 470 nm; Albedo at 471 nm; Albedo at 472 nm; Albedo at 473 nm; Albedo at 474 nm; Albedo at 475 nm; Albedo at 476 nm; Albedo at 477 nm; Albedo at 478 nm; Albedo at 479 nm; Albedo at 480 nm; Albedo at 481 nm; Albedo at 482 nm; Albedo at 483 nm; Albedo at 484 nm; Albedo at 485 nm; Albedo at 486 nm; Albedo at 487 nm; Albedo at 488 nm; Albedo at 489 nm; Albedo at 490 nm; Albedo at 491 nm; Albedo at 492 nm; Albedo at 493 nm; Albedo at 494 nm; Albedo at 495 nm; Albedo at 496 nm; Albedo at 497 nm; Albedo at 498 nm; Albedo at 499 nm; Albedo at 500 nm; Albedo at 501 nm; Albedo at 502 nm; Albedo at 503 nm; Albedo at 504 nm; Albedo at 505 nm; Albedo at 506 nm; Albedo at 507 nm; Albedo at 508 nm; Albedo at 509 nm; Albedo at 510 nm; Albedo at 511 nm; Albedo at 512 nm; Albedo at 513 nm; Albedo at 514 nm; Albedo at 515 nm; Albedo at 516 nm; Albedo at 517 nm; Albedo at 518 nm; Albedo at 519 nm; Albedo at 520 nm; Albedo at 521 nm; Albedo at 522 nm; Albedo at 523 nm; Albedo at 524 nm; Albedo at 525 nm; Albedo at 526 nm; Albedo at 527 nm; Albedo at 528 nm; Albedo at 529 nm; Albedo at 530 nm; Albedo at 531 nm; Albedo at 532 nm; Albedo at 533 nm; Albedo at 534 nm; Albedo at 535 nm; Albedo at 536 nm; Albedo at 537 nm; Albedo at 538 nm; Albedo at 539 nm; Albedo at 540 nm; Albedo at 541 nm; Albedo at 542 nm; Albedo at 543 nm; Albedo at 544 nm; Albedo at 545 nm; Albedo at 546 nm; Albedo at 547 nm; Albedo at 548 nm; Albedo at 549 nm; Albedo at 550 nm; Albedo at 551 nm; Albedo at 552 nm; Albedo at 553 nm; Albedo at 554 nm; Albedo at 555 nm; Albedo at 556 nm; Albedo at 557 nm; Albedo at 558 nm; Albedo at 559 nm; Albedo at 560 nm; Albedo at 561 nm; Albedo at 562 nm; Albedo at 563 nm; Albedo at 564 nm; Albedo at 565 nm; Albedo at 566 nm; Albedo at 567 nm; Albedo at 568 nm; Albedo at 569 nm; Albedo at 570 nm; Albedo at 571 nm; Albedo at 572 nm; Albedo at 573 nm; Albedo at 574 nm; Albedo at 575 nm; Albedo at 576 nm; Albedo at 577 nm; Albedo at 578 nm; Albedo at 579 nm; Albedo at 580 nm; Albedo at 581 nm; Albedo at 582 nm; Albedo at 583 nm; Albedo at 584 nm; Albedo at 585 nm; Albedo at 586 nm; Albedo at 587 nm; Albedo at 588 nm; Albedo at 589 nm; Albedo at 590 nm; Albedo at 591 nm; Albedo at 592 nm; Albedo at 593 nm; Albedo at 594 nm; Albedo at 595 nm; Albedo at 596 nm; Albedo at 597 nm; Albedo at 598 nm; Albedo at 599 nm; Albedo at 600 nm; Albedo at 601 nm; Albedo at 602 nm; Albedo at 603 nm; Albedo at 604 nm; Albedo at 605 nm; Albedo at 606 nm; Albedo at 607 nm; Albedo at 608 nm; Albedo at 609 nm; Albedo at 610 nm; Albedo at 611 nm; Albedo at 612 nm; Albedo at 613 nm; Albedo at 614 nm; Albedo at 615 nm; Albedo at 616 nm; Albedo at 617 nm; Albedo at 618 nm; Albedo at 619 nm; Albedo at 620 nm; Albedo at 621 nm; Albedo at 622 nm; Albedo at 623 nm; Albedo at 624 nm; Albedo at 625 nm; Albedo at 626 nm; Albedo at 627 nm; Albedo at 628 nm; Albedo at 629 nm; Albedo at 630 nm; Albedo at 631 nm; Albedo at 632 nm; Albedo at 633 nm; Albedo at 634 nm; Albedo at 635 nm; Albedo at 636 nm; Albedo at 637 nm; Albedo at 638 nm; Albedo at 639 nm; Albedo at 640 nm; Albedo at 641 nm; Albedo at 642 nm; Albedo at 643 nm; Albedo at 644 nm; Albedo at 645 nm; Albedo at 646 nm; Albedo at 647 nm; Albedo at 648 nm; Albedo at 649 nm; Albedo at 650 nm; Albedo at 651 nm; Albedo at 652 nm; Albedo at 653 nm; Albedo at 654 nm; Albedo at 655 nm; Albedo at 656 nm; Albedo at 657 nm; Albedo at 658 nm; Albedo at 659 nm; Albedo at 660 nm; Albedo at 661 nm; Albedo at 662 nm; Albedo at 663 nm; Albedo at 664 nm; Albedo at 665 nm; Albedo at 666 nm; Albedo at 667 nm; Albedo at 668 nm; Albedo at 669 nm; Albedo at 670 nm; Albedo at 671 nm; Albedo at 672 nm; Albedo at 673 nm; Albedo at 674 nm; Albedo at 675 nm; Albedo at 676 nm; Albedo at 677 nm; Albedo at 678 nm; Albedo at 679 nm; Albedo at 680 nm; Albedo at 681 nm; Albedo at 682 nm; Albedo at 683 nm; Albedo at 684 nm; Albedo at 685 nm; Albedo at 686 nm; Albedo at 687 nm; Albedo at 688 nm; Albedo at 689 nm; Albedo at 690 nm; Albedo at 691 nm; Albedo at 692 nm; Albedo at 693 nm; Albedo at 694 nm; Albedo at 695 nm; Albedo at 696 nm; Albedo at 697 nm; Albedo at 698 nm; Albedo at 699 nm; Albedo at 700 nm; Albedo at 701 nm; Albedo at 702 nm; Albedo at 703 nm; Albedo at 704 nm; Albedo at 705 nm; Albedo at 706 nm; Albedo at 707 nm; Albedo at 708 nm; Albedo at 709 nm; Albedo at 710 nm; Albedo at 711 nm; Albedo at 712 nm; Albedo at 713 nm; Albedo at 714 nm; Albedo at 715 nm; Albedo at 716 nm; Albedo at 717 nm; Albedo at 718 nm; Albedo at 719 nm; Albedo at 720 nm; Albedo at 721 nm; Albedo at 722 nm; Albedo at 723 nm; Albedo at 724 nm; Albedo at 725 nm; Albedo at 726 nm; Albedo at 727 nm; Albedo at 728 nm; Albedo at 729 nm; Albedo at 730 nm; Albedo at 731 nm; Albedo at 732 nm; Albedo at 733 nm; Albedo at 734 nm; Albedo at 735 nm; Albedo at 736 nm; Albedo at 737 nm; Albedo at 738 nm; Albedo at 739 nm; Albedo at 740 nm; Albedo at 741 nm; Albedo at 742 nm; Albedo at 743 nm; Albedo at 744 nm; Albedo at 745 nm; Albedo at 746 nm; Albedo at 747 nm; Albedo at 748 nm; Albedo at 749 nm; Albedo at 750 nm; Albedo at 751 nm; Albedo at 752 nm; Albedo at 753 nm; Albedo at 754 nm; Albedo at 755 nm; Albedo at 756 nm; Albedo at 757 nm; Albedo at 758
    Type: Dataset
    Format: text/tab-separated-values, 727332 data points
    Location Call Number Expected Availability
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  • 98
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; BRS; buoy; Buoy, radiation station; Calculated; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Ice mass balance; Irradiance, incident; Irradiance, incident, photosynthetically active; Irradiance, incident, photosynthetically active, absolute; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Quality flag, sun elevation; Sea Ice Physics @ AWI; snow depth; solar radiation; Spectral irradiance, incident at 320 nm; Spectral irradiance, incident at 321 nm; Spectral irradiance, incident at 322 nm; Spectral irradiance, incident at 323 nm; Spectral irradiance, incident at 324 nm; Spectral irradiance, incident at 325 nm; Spectral irradiance, incident at 326 nm; Spectral irradiance, incident at 327 nm; Spectral irradiance, incident at 328 nm; Spectral irradiance, incident at 329 nm; Spectral irradiance, incident at 330 nm; Spectral irradiance, incident at 331 nm; Spectral irradiance, incident at 332 nm; Spectral irradiance, incident at 333 nm; Spectral irradiance, incident at 334 nm; Spectral irradiance, incident at 335 nm; Spectral irradiance, incident at 336 nm; Spectral irradiance, incident at 337 nm; Spectral irradiance, incident at 338 nm; Spectral irradiance, incident at 339 nm; Spectral irradiance, incident at 340 nm; Spectral irradiance, incident at 341 nm; Spectral irradiance, incident at 342 nm; Spectral irradiance, incident at 343 nm; Spectral irradiance, incident at 344 nm; Spectral irradiance, incident at 345 nm; Spectral irradiance, incident at 346 nm; Spectral irradiance, incident at 347 nm; Spectral irradiance, incident at 348 nm; Spectral irradiance, incident at 349 nm; Spectral irradiance, incident at 350 nm; Spectral irradiance, incident at 351 nm; Spectral irradiance, incident at 352 nm; Spectral irradiance, incident at 353 nm; Spectral irradiance, incident at 354 nm; Spectral irradiance, incident at 355 nm; Spectral irradiance, incident at 356 nm; Spectral irradiance, incident at 357 nm; Spectral irradiance, incident at 358 nm; Spectral irradiance, incident at 359 nm; Spectral irradiance, incident at 360 nm; Spectral irradiance, incident at 361 nm; Spectral irradiance, incident at 362 nm; Spectral irradiance, incident at 363 nm; Spectral irradiance, incident at 364 nm; Spectral irradiance, incident at 365 nm; Spectral irradiance, incident at 366 nm; Spectral irradiance, incident at 367 nm; Spectral irradiance, incident at 368 nm; Spectral irradiance, incident at 369 nm; Spectral irradiance, incident at 370 nm; Spectral irradiance, incident at 371 nm; Spectral irradiance, incident at 372 nm; Spectral irradiance, incident at 373 nm; Spectral irradiance, incident at 374 nm; Spectral irradiance, incident at 375 nm; Spectral irradiance, incident at 376 nm; Spectral irradiance, incident at 377 nm; Spectral irradiance, incident at 378 nm; Spectral irradiance, incident at 379 nm; Spectral irradiance, incident at 380 nm; Spectral irradiance, incident at 381 nm; Spectral irradiance, incident at 382 nm; Spectral irradiance, incident at 383 nm; Spectral irradiance, incident at 384 nm; Spectral irradiance, incident at 385 nm; Spectral irradiance, incident at 386 nm; Spectral irradiance, incident at 387 nm; Spectral irradiance, incident at 388 nm; Spectral irradiance, incident at 389 nm; Spectral irradiance, incident at 390 nm; Spectral irradiance, incident at 391 nm; Spectral irradiance, incident at 392 nm; Spectral irradiance, incident at 393 nm; Spectral irradiance, incident at 394 nm; Spectral irradiance, incident at 395 nm; Spectral irradiance, incident at 396 nm; Spectral irradiance, incident at 397 nm; Spectral irradiance, incident at 398 nm; Spectral irradiance, incident at 399 nm; Spectral irradiance, incident at 400 nm; Spectral irradiance, incident at 401 nm; Spectral irradiance, incident at 402 nm; Spectral irradiance, incident at 403 nm; Spectral irradiance, incident at 404 nm; Spectral irradiance, incident at 405 nm; Spectral irradiance, incident at 406 nm; Spectral irradiance, incident at 407 nm; Spectral irradiance, incident at 408 nm; Spectral irradiance, incident at 409 nm; Spectral irradiance, incident at 410 nm; Spectral irradiance, incident at 411 nm; Spectral irradiance, incident at 412 nm; Spectral irradiance, incident at 413 nm; Spectral irradiance, incident at 414 nm; Spectral irradiance, incident at 415 nm; Spectral irradiance, incident at 416 nm; Spectral irradiance, incident at 417 nm; Spectral irradiance, incident at 418 nm; Spectral irradiance, incident at 419 nm; Spectral irradiance, incident at 420 nm; Spectral irradiance, incident at 421 nm; Spectral irradiance, incident at 422 nm; Spectral irradiance, incident at 423 nm; Spectral irradiance, incident at 424 nm; Spectral irradiance, incident at 425 nm; Spectral irradiance, incident at 426 nm; Spectral irradiance, incident at 427 nm; Spectral irradiance, incident at 428 nm; Spectral irradiance, incident at 429 nm; Spectral irradiance, incident at 430 nm; Spectral irradiance, incident at 431 nm; Spectral irradiance, incident at 432 nm; Spectral irradiance, incident at 433 nm; Spectral irradiance, incident at 434 nm; Spectral irradiance, incident at 435 nm; Spectral irradiance, incident at 436 nm; Spectral irradiance, incident at 437 nm; Spectral irradiance, incident at 438 nm; Spectral irradiance, incident at 439 nm; Spectral irradiance, incident at 440 nm; Spectral irradiance, incident at 441 nm; Spectral irradiance, incident at 442 nm; Spectral irradiance, incident at 443 nm; Spectral irradiance, incident at 444 nm; Spectral irradiance, incident at 445 nm; Spectral irradiance, incident at 446 nm; Spectral irradiance, incident at 447 nm; Spectral irradiance, incident at 448 nm; Spectral irradiance, incident at 449 nm; Spectral irradiance, incident at 450 nm; Spectral irradiance, incident at 451 nm; Spectral irradiance, incident at 452 nm; Spectral irradiance, incident at 453 nm; Spectral irradiance, incident at 454 nm; Spectral irradiance, incident at 455 nm; Spectral irradiance, incident at 456 nm; Spectral irradiance, incident at 457 nm; Spectral irradiance, incident at 458 nm; Spectral irradiance, incident at 459 nm; Spectral irradiance, incident at 460 nm; Spectral irradiance, incident at 461 nm; Spectral irradiance, incident at 462 nm; Spectral irradiance, incident at 463 nm; Spectral irradiance, incident at 464 nm; Spectral irradiance, incident at 465 nm; Spectral irradiance, incident at 466 nm; Spectral irradiance, incident at 467 nm; Spectral irradiance, incident at 468 nm; Spectral irradiance, incident at 469 nm; Spectral irradiance, incident at 470 nm; Spectral irradiance, incident at 471 nm; Spectral irradiance, incident at 472 nm; Spectral irradiance, incident at 473 nm; Spectral irradiance, incident at 474 nm; Spectral irradiance, incident at 475 nm; Spectral irradiance, incident at 476 nm; Spectral irradiance, incident at 477 nm; Spectral irradiance, incident at 478 nm; Spectral irradiance, incident at 479 nm; Spectral irradiance, incident at 480 nm; Spectral irradiance, incident at 481 nm; Spectral irradiance, incident at 482 nm; Spectral irradiance, incident at 483 nm; Spectral irradiance, incident at 484 nm; Spectral irradiance, incident at 485 nm; Spectral irradiance, incident at 486 nm; Spectral irradiance, incident at 487 nm; Spectral irradiance, incident at 488 nm; Spectral irradiance, incident at 489 nm; Spectral irradiance, incident at 490 nm; Spectral irradiance, incident at 491 nm; Spectral irradiance, incident at 492 nm; Spectral irradiance, incident at 493 nm; Spectral irradiance, incident at 494 nm; Spectral irradiance, incident at 495 nm; Spectral irradiance, incident at 496 nm; Spectral irradiance, incident at 497 nm; Spectral irradiance, incident at 498 nm;
    Type: Dataset
    Format: text/tab-separated-values, 955680 data points
    Location Call Number Expected Availability
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  • 99
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; Battery, voltage; BRS; buoy; Buoy, radiation station; chlorophyll; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Humidity, relative, technical; Ice mass balance; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; Pressure, atmospheric; PS122/1_1-167, 2019R8; Quality flag, position; Sea Ice Physics @ AWI; snow depth; solar radiation; Temperature, technical
    Type: Dataset
    Format: text/tab-separated-values, 34050 data points
    Location Call Number Expected Availability
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  • 100
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2024-03-05
    Description: Solar radiation over and under sea ice was measured by radiation station 2019R8, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 05 October 2019 and 31 July 2020 in sample intervals of 3 hours. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance. Along with the radiation measurements, this autonomous platform consisted of a 5 m long thermistor chain with sensor spacing of 0.02 m and several other sensor packages, which measured water temperature, pressure and conductivity at hourly intervals. Ecology sensors measured backscatter strength, chlorophyll a and fluorescence of dissolved organic matter at hourly intervals. Oxygen sensors measured relative oxygen air saturation, and water temperature at hourly intervals. In addition, relative snow height was measured at hourly intervals. All times are given in UTC.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_88; Akademik Fedorov; Arctic Ocean; autonomous platform; AWI_SeaIce; Backscatter; Backscatter strength; BRS; buoy; Buoy, radiation station; chlorophyll; Chlorophyll a; Conductivity; Current sea ice maps for Arctic and Antarctic; DATE/TIME; drift; FDOM; Fluorescence, dissolved organic matter; Ice mass balance; LATITUDE; LONGITUDE; meereisportal.de; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oxygen; PS122/1_1-167, 2019R8; Quality flag, position; Sea Ice Physics @ AWI; snow depth; solar radiation
    Type: Dataset
    Format: text/tab-separated-values, 116176 data points
    Location Call Number Expected Availability
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